Detecting breast cancer

ABSTRACT

Provided herein is technology for breast cancer screening and particularly, but not exclusively, to methods, compositions, and related uses for detecting the presence of breast cancer.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No. 16/202,944, filed Nov. 28, 2018, allowed as U.S. Pat. No. 10,934,594, which claims priority to and the benefit of U.S. Provisional Application No. 62/592,828, filed Nov. 30, 2017, the contents of which are hereby incorporated by reference in their entireties.

FIELD OF INVENTION

Provided herein is technology for breast cancer screening and particularly, but not exclusively, to methods, compositions, and related uses for detecting the presence of breast cancer.

BACKGROUND

Breast cancer affects approximately 230,000 US women per year and claims about 40,000 lives every year. Although carriers of germline mutations in BRCA1 and BRCA2 genes are known to be at high risk of breast cancer, most women who get breast cancer do not have a mutation in one of these genes and there is limited ability to accurately identify women at increased risk of breast cancer. Effective prevention therapies exist, but current risk prediction models do not accurately identify the majority of women at increased risk of breast cancer (see, e.g., Pankratz V S, et al., J Clin Oncol 2008 Nov. 20; 26(33):5374-9).

Improved methods for detecting breast cancer are needed.

The present invention addresses these needs.

SUMMARY

Methylated DNA has been studied as a potential class of biomarkers in the tissues of most tumor types. In many instances, DNA methyltransferases add a methyl group to DNA at cytosine-phosphate-guanine (CpG) island sites as an epigenetic control of gene expression. In a biologically attractive mechanism, acquired methylation events in promoter regions of tumor suppressor genes are thought to silence expression, thus contributing to oncogenesis. DNA methylation may be a more chemically and biologically stable diagnostic tool than RNA or protein expression (Laird (2010) Nat Rev Genet 11: 191-203). Furthermore, in other cancers like sporadic colon cancer, methylation markers offer excellent specificity and are more broadly informative and sensitive than are individual DNA mutations (Zou et al (2007) Cancer Epidemiol Biomarkers Prev 16: 2686-96).

Analysis of CpG islands has yielded important findings when applied to animal models and human cell lines. For example, Zhang and colleagues found that amplicons from different parts of the same CpG island may have different levels of methylation (Zhang et al. (2009) PLoS Genet 5: e1000438). Further, methylation levels were distributed bi-modally between highly methylated and unmethylated sequences, further supporting the binary switch-like pattern of DNA methyltransferase activity (Zhang et al. (2009) PLoS Genet 5: e1000438). Analysis of murine tissues in vivo and cell lines in vitro demonstrated that only about 0.3% of high CpG density promoters (HCP, defined as having >7% CpG sequence within a 300 base pair region) were methylated, whereas areas of low CpG density (LCP, defined as having <5% CpG sequence within a 300 base pair region) tended to be frequently methylated in a dynamic tissue-specific pattern (Meissner et al. (2008) Nature 454: 766-70). HCPs include promoters for ubiquitous housekeeping genes and highly regulated developmental genes. Among the HCP sites methylated at >50% were several established markers such as Wnt 2, NDRG2, SFRP2, and BMP3 (Meissner et al. (2008) Nature 454: 766-70).

Epigenetic methylation of DNA at cytosine-phosphate-guanine (CpG) island sites by DNA methyltransferases has been studied as a potential class of biomarkers in the tissues of most tumor types. In a biologically attractive mechanism, acquired methylation events in promotor regions of tumor suppressor genes are thought to silence expression, contributing to oncogenesis. DNA methylation may be a more chemically and biologically stable diagnostic tool than RNA or protein expression. Furthermore, in other cancers like sporadic colon cancer, aberrant methylation markers are more broadly informative and sensitive than are individual DNA mutations and offer excellent specificity.

Several methods are available to search for novel methylation markers. While microarray based interrogation of CpG methylation is a reasonable, high-throughput approach, this strategy is biased towards known regions of interest, mainly established tumor suppressor promotors. Alternative methods for genome-wide analysis of DNA methylation have been developed in the last decade. There are three basic approaches. The first employs digestion of DNA by restriction enzymes which recognize specific methylated sites, followed by several possible analytic techniques which provide methylation data limited to the enzyme recognition site or the primers used to amplify the DNA in quantification steps (such as methylation-specific PCR; MSP). A second approach enriches methylated fractions of genomic DNA using anti-bodies directed to methyl-cytosine or other methylation-specific binding domains followed by microarray analysis or sequencing to map the fragment to a reference genome. This approach does not provide single nucleotide resolution of all methylated sites within the fragment. A third approach begins with bisulfite treatment of the DNA to convert all unmethylated cytosines to uracil, followed by restriction enzyme digestion and complete sequencing of all fragments after coupling to an adapter ligand. The choice of restriction enzymes can enrich the fragments for CpG dense regions, reducing the number of redundant sequences which may map to multiple gene positions during analysis.

RRBS yields CpG methylation status data at single nucleotide resolution of 80-90% of all CpG islands and a majority of tumor suppressor promoters at medium to high read coverage. In cancer case—control studies, analysis of these reads results in the identification of differentially methylated regions (DMRs). In previous RRBS analysis of pancreatic cancer specimens, hundreds of DMRs were uncovered, many of which had never been associated with carcinogenesis and many of which were unannotated. Further validation studies on independent tissue samples sets confirmed marker CpGs which were 100% sensitive and specific in terms of performance.

Provided herein is technology for breast cancer screening and particularly, but not exclusively, to methods, compositions, and related uses for detecting the presence of breast cancer.

Indeed, as described in Examples I, II and III, experiments conducted during the course for identifying embodiments for the present invention identified a novel set of differentially methylated regions (DMRs) for discriminating cancer of the breast derived DNA from non-neoplastic control DNA.

Such experiments list and describe 327 novel DNA methylation markers distinguishing breast cancer tissue from benign breast tissue (see, Table 2, Examples I, II and III).

From these 327 novel DNA methylation markers, further experiments identified the following markers and/or panels of markers capable of distinguishing triple negative breast cancer tissue from benign breast tissue:

-   -   ABLIM1, AJAP1_B, ASCL2, ATP6V1B1, BANK1, CALN1_A, CALN1_B,         CLIC6, DSCR6, FOXP4, GAD2, GCGR, GP5, GRASP, HBM, HNF1B_B,         KLF16, MAGI2, MAX.chr11.14926602-14927148,         MAX.chr12.4273906-4274012, MAX.chr17.73073682-73073814,         MAX.chr18.76734362-76734370, MAX.chr2.97193478-97193562,         MAX.chr22.42679578-42679917, MAX.chr4.8859253-8859329,         MAX.chr4.8859602-8859669, MAX.chr4.8860002-8860038,         MAX.chr5.145725410-145725459, MAX.chr6.157557371-157557657, MPZ,         NKX2-6, PDX1, PLXNC1_A, PPARG, PRKCB, PTPRN2, RBFOX_A, SCRT2_A,         SLC7A4, STAC2_B, STX16_A, STX16_B, TBX1, TRH_A, VSTM2B_A,         ZBTB16, ZNF132, and ZSCAN23 (see, Table 3, Example I);     -   CALN1_A, LOC100132891, NACAD, TRIM67, ATP6V1B1, DLX4, GP5,         ITPRIPL1, MAX.chr11.14926602-14927148,         MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ,         PRKCB, ST8SIA4, STX16_B ITPRIPL1, KLF16,         MAX.chr12.4273906-4274012, KCNK9, SCRT2_B, CDH4_E, HNF1B_B,         TRH_A, MAX.chr20.1784209-1784461, MAX.chr12.4273906-4274012,         MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, and         DSCR6 (see, Table 11, Example I);     -   ATP6V1B1, MAX.chr11.14926602-14927148, PRKCB, TRH_A, MPZ, GP5,         TRIM67, MAX.chr12.4273906-4274012, CALN1_A,         MAX.chr12.4273906-4274012, MAX.chr5.42994866-42994936, SCRT2_B,         MAX.chr5.145725410-145725459, BHLHE23_D,         MAX.chr5.77268672-77268725, EMX1_A, DSCR6, and DLX4 (see, Table         16A, Example II).

From these 327 novel DNA methylation markers, further experiments identified the following markers and/or panels of markers capable of distinguishing HER2⁺ breast cancer tissue from benign breast tissue:

-   -   ABLIM1, AFAP1L1, AKR1B1, ALOX5, AMN, ARL5C, BANK1, BCAT1,         BEGAIN, BEST4, BHLHE23_B, BHLHE23_C, C17orf64, C1QL2, C7orf52,         CALN1_B, CAV2, CD8A, CDH4_A, CDH4_B, CDH4_C, CDH4_D, CDH4_E,         CDH4_F, CHST2_B, CLIP4, CR1, DLK1, DNAJC6, DNM3_A, EMX1_A, ESPN,         FABP5, FAM150A, FLJ42875, GLP1R, GNG4, GYPC_A, HAND2, HES5,         HNF1B_A, HNF1B_B, HOXA1_A, HOXA1_B, HOXA7_A, HOXA7_B, HOXA7_C,         HOXD9, IGF2BP3_A, IGF2BP3_B, IGSF9B_A, IL15RA, INSM1, ITPKA_B,         ITPRIPL1, KCNE3, KCNK17_B, LIME1, LOC100132891, LOC283999, LY6H,         MAST1, MAX.chr1.158083198-158083476,         MAX.chr1.228074764-228074977, MAX.chr1.46913931-46913950,         MAX.chr10.130085265-130085312, MAX.chr11.68622869-68622968,         MAX.chr14.101176106-101176260, MAX.chr15.96889069-96889128,         MAX.chr17.8230197-8230314, MAX.chr19.46379903-46380197,         MAX.chr2.97193163-97193287, MAX.chr2.97193478-97193562,         MAX.chr20.1784209-1784461, MAX.chr21.44782441-44782498,         MAX.chr22.23908718-23908782, MAX.chr5.145725410-145725459,         MAX.chr5.178957564-178957598, MAX.chr5.180101084-180101094,         MAX.chr5.42952185-42952280, MAX.chr5.42994866-42994936,         MAX.chr6.27064703-27064783, MAX.chr7.152622607-152622638,         MAX.chr8.145104132-145104218, MAX.chr9.136474504-136474527,         MCF2L2, MSX2P1, NACAD, NID2_B, NID2_C, ODC1, OSR2_B, PAQR6,         PCDH8, PIF1, PPARA, PPP2R5C, PRDM13_A, PRHOXNB, PRKCB, RBFOX3_A,         RBFOX3_B, RFX8, SNCA, STAC2_A, STAC2_B, STX16_B SYT5, TIMP2,         TMEFF2, TNFRSF10D, TRH_B, TRIM67, TRIM71_C, USP44_A, USP44_B,         UTF1, UTS2R, VSTM2B_A, VSTM2B_B, ZFP64, and ZNF132 (see, Table         4, Example I);     -   BHLHE23_C, CALN1_A, CD1D, CHST2_A, FMN2, HOXA1_A, HOXA7_A,         KCNH8, LOC100132891, MAX.chr15.96889013-96889128, NACAD, TRIM67,         ATP6V1B1, C17orf64, CHST2_B, DLX4, DNM3_A, EMX1_A, IGF2BP3_A,         IGF2BP3_B, ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148,         MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ,         ODC1, PLXNC1_A, PRKCB, LOC100132891, ITPRIPL1, ABLIM1,         MAX.chr12.4273906-4274012, MAX.chr19.46379903-46380197, ZSCAN12,         BHLHE23_D, COL23A1, KCNK9, LAYN, PLXNC1_A, RIC3, SCRT2_B, ALOX5,         CDH4_E, HNF1B_B, TRH_A, MAST1, ASCL2, MAX.chr20.1784209-1784461,         RBFOX_A, MAX.chr12.4273906-4274012, GAS7,         MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725,         GYPC_B, DLX6, FBN1, OSR2_A, BEST4, AJAP1_B, DSCR6, and         MAX.chr11.68622869-68622968 (see, Table 11, Example I);     -   ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148,         UBTF, PRKCB, TRH_A, MPZ, GP5, DNM3_A, TRIM67, PLXNC1_A,         MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1,         MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936,         OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459,         MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395,         MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_C, ALOX5,         MAX.chr19.46379903-46380197, ODC1, CHST2_A,         MAX.chr5.77268672-77268725, C17orf64, EMX1_A, CHST2_B, DSCR6,         ITPRIPL1, IGF2BP3_B, DLX4, ABLIM1, BHLHE23_D, ZSCAN12, GRASP,         C10orf125 (see, Table 16B, Example II).

From these 327 novel DNA methylation markers, further experiments identified the following markers and/or panels of markers capable of distinguishing Luminal A breast cancer tissue from benign breast tissue:

-   -   ARL5C, BHLHE23_C, BMP6, C10orf125, C17orf64, C19orf66, CAMKV,         CD1D, CDH4_E, CDH4_F, CHST2_A, CRHBP, DLX6, DNM3_A, DNM3_B,         DNM3_C, ESYT3, ETS1_A, ETS1_B, FAM126A, FAM189A1, FAM20A,         FAM59B, FBN1, FLRT2, FMN2, FOXP4, GAS7, GYPC_A, GYPC_B, HAND2,         HES5, HMGA2, HNF1B_B, IGF2BP3_A, IGF2BP3_B, KCNH8, KCNK17_A,         KCNQ2, KLHDC7B, LOC100132891, MAX.chr1.46913931-46913950,         MAX.chr11.68622869-68622968, MAX.chr12.4273906-4274012,         MAX.chr12.59990591-59990895, MAX.chr17.73073682-73073814,         MAX.chr20.1783841-1784054, MAX.chr21.47063802-47063851,         MAX.chr4.8860002-8860038, MAX.chr5.172234248-172234494,         MAX.chr5.178957564-178957598, MAX.chr6.130686865-130686985,         MAX.chr8.687688-687736, MAX.chr8.688863-688924,         MAX.chr9.114010-114207, MPZ, NID2_A, NKX2-6, ODC1, OSR2_A,         POU4F1, PRDM13_B, PRKCB, RASGRF2, RIPPLY2, SLC30A10, ST8SIA4,         SYN2, TRIM71_A, TRIM71_B, TRIM71_C, UBTF, ULBP1, USP44_B, and         VSTM2B_A (see, Table 5, Example I);     -   BHLHE23_C, CD1D, CHST2_A, FAM126A, FMN2, HOXA1_A, HOXA7_A,         KCNH8, LOC100132891, MAX.chr15.96889013-96889128, SLC30A10,         TRIM67, ATP6V1B1, BANK1, C10orf125, C17orf64, CHST2_B, DNM3_A,         EMX1_A, GP5, IGF2BP3_A, IGF2BP3_B, ITPRIPL1, LMX1B_A,         MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936,         MAX.chr8.124173030-124173395, MPZ, ODC1, PLXNC1_A, PRKCB,         ST8SIA4, STX16_B UBTF, LOC100132891, ITPRIPL1,         MAX.chr12.4273906-4274012, MAX.chr12.59990671-59990859,         BHLHE23_D, COL23A1, KCNK9, OTX1, PLXNC1_A, HNF1B_B, MAST1,         ASCL2, MAX.chr20.1784209-1784461, RBFOX_A,         MAX.chr12.4273906-4274012, GAS7, MAX.chr5.145725410-145725459,         MAX.chr5.77268672-77268725, GYPC_B, DLX6, FBN1, OSR2_A, BEST4,         DSCR6, MAX.chr11.68622869-68622968 (see, Table 11, Example I);     -   ATP6V1B1, LMX1B_A, BANK1, OTX1, ST8SIA4,         MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A,         TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1,         MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936,         OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459,         MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395,         MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, ALOX5,         MAX.chr19.46379903-46380197, ODC1, CHST2_A,         MAX.chr5.77268672-77268725, C17orf64, EMX1_A, CHST2_B, ITPRIPL1,         IGF2BP3_B, CDH4_E, ABLIM1, SLC30A10, C10orf25 (see, Table 16C,         Example II).

From these 327 novel DNA methylation markers, further experiments identified the following markers and/or panels of markers capable of distinguishing Luminal B breast cancer tissue from benign breast tissue:

-   -   ACCN1, AJAP1_A, AJAP1_B, BEST4, CALN1_B, CBLN1_B, CDH4_E, DLX4,         FOXP4, IGSF9B_B, ITPRIPL1, KCNA1, KLF16, LMX1B_A, MAST1,         MAX.chr11.14926602-14927148, MAX.chr17.73073682-73073814,         MAX.chr18.76734362-76734370, MAX.chr18.76734423-76734476,         MAX.chr19.30719261-30719354, MAX.chr22.42679578-42679917,         MAX.chr4.8860002-8860038, MAX.chr5.145725410-145725459,         MAX.chr5.178957564-178957598, MAX.chr5.77268672-77268725,         MAX.chr8.124173128-124173268, MPZ, PPARA, PRMT1, RBFOX3_B,         RYR2_A, SALL3, SCRT2_A, SPHK2, STX16_B SYNJ2, TMEM176A, TSHZ3,         and VIPR2 (see, Table 6, Example I);     -   CALN1_A, LOC100132891, MAX.chr15.96889013-96889128, ATP6V1B1,         C17orf64, DLX4, ITPRIPL1, MAX.chr11.14926602-14927148,         MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ,         PRKCB, ITPRIPL1, KLF16, MAX.chr12.4273906-4274012,         MAX.chr19.46379903-46380197, BHLHE23_D, HNF1B_B, TRH_A, ASCL2,         MAX.chr20.1784209-1784461, MAX.chr12.4273906-4274012,         MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, BEST4,         AJAP1_B, and DSCR6 (see, Table 11, Example I);     -   ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148,         UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, PLXNC1_A,         MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1,         MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936,         OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459,         MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395,         MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_C, ALOX5,         MAX.chr19.46379903-46380197, CHST2_B,         MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1,         IGF2BP3_B, CDH4_E, DLX4, ABLIM1, BHLHE23_D (see, Table 16D,         Example II).

From these 327 novel DNA methylation markers, further experiments identified the following markers and/or panels of markers capable of distinguishing BRCA1 breast cancer tissue from benign breast tissue:

-   -   C10orf93, C20orf195_A, C20orf195_B, CALN1_B, CBLN1_A, CBLN1_B,         CCDC61, CCND2_A, CCND2_B, CCND2_C, EMX1_B, FAM150B, GRASP, HBM,         ITPRIPL1, KCNK17_A, KIAA1949, LOC100131176, MAST1,         MAX.chr1.8277285-8277316, MAX.chr1.8277479-8277527,         MAX.chr11.14926602-14926729, MAX.chr11.14926860-14927148,         MAX.chr15.96889013-96889128, MAX.chr18.5629721-5629791,         MAX.chr19.30719261-30719354, MAX.chr22.42679767-42679917,         MAX.chr5.178957564-178957598, MAX.chr5.77268672-77268725,         MAX.chr6.157556793-157556856, MAX.chr8.124173030-124173395, MN1,         MPZ, NR2F6, PDXK_A, PDXK_B, PTPRM, RYR2_B, SERPINB9_A,         SERPINB9_B, SLC8A3, STX16_B TEPP, TOX, VIPR2, VSTM2B_A, ZNF486,         ZNF626, and ZNF671 (see, Table 7, Example I);     -   BHLHE23_C, CALN1_A, CD1D, HOXA7_A, LOC100132891,         MAX.chr1.8277479-8277527, MAX.chr15.96889013-96889128, NACAD,         ATP6V1B1, BANK1, C17orf64, DLX4, EMX1_A, FOXP4, GP5, ITPRIPL1,         LMX1B_A, MAX.chr11.14926602-14927148,         MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ,         PRKCB, STX16_B UBTF, LOC100132891, ITPRIPL1, ABLIM1,         MAX.chr19.46379903-46380197, ZSCAN12, BHLHE23_D, CXCL12, KCNK9,         OTX1, RIC3, SCRT2_B, MAX.chr17.73073682-73073814, CDH4_E,         HNF1B_B, TRH_A, MAX.chr20.1784209-1784461,         MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, BEST4,         and DSCR6 (see, Table 11, Example I);

From these 327 novel DNA methylation markers, further experiments identified the following markers and/or panels of markers capable of distinguishing BRCA2 breast cancer tissue from benign breast tissue:

-   -   ANTXR2, B3GNT5, BHLHE23_C, BMP4, CHRNA7, EPHA4, FAM171A1,         FAM20A, FMNL2, FSCN1, GSTP1, HBM, IGFBP5, IL17REL, ITGA9,         ITPRIPL1, KIRREL2, LRRC34, MAX.chr1.239549742-239549886,         MAX.chr1.8277479-8277527, MAX.chr11.14926602-14926729,         MAX.chr11.14926860-14927148, MAX.chr15.96889013-96889128,         MAX.chr2.238864674-238864735, MAX.chr5.81148300-81148332,         MAX.chr7.151145632-151145743, MAX.chr8.124173030-124173395,         MAX.chr8.143533298-143533558, MERTK, MPZ, NID2_C, NTRK3,         OLIG3_A, OLIG3_B, OSR2_C, PROM1, RGS17, SBNO2, STX16_B TBKBP1,         TLX1NB, VIPR2, VN1R2, VSNL1, and ZFP64 (see, Table 8, Example         I);     -   MAX.chr15.96889013-96889128, ATP6V1B1, C17orf64, ITPRIPL1,         MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936,         LOC100132891, ITPRIPL1, ABLIM1, MAX.chr19.46379903-46380197,         COL23A1, LAYN, OTX1, TRH_A, MAX.chr5.145725410-145725459,         MAX.chr11.68622869-68622968 (see, Table 11, Example I).

From these 327 novel DNA methylation markers, further experiments identified the following markers and/or panels of markers capable of distinguishing invasive breast cancer tissue from benign breast tissue:

-   -   CDH4_E, FLJ42875, GAD2, GRASP, ITPRIPL1, KCNA1,         MAX.chr12.4273906-4274012, MAX.chr18.76734362-76734370,         MAX.chr18.76734423-76734476, MAX.chr19.30719261-30719354,         MAX.chr4.8859602-8859669, MAX.chr4.8860002-8860038,         MAX.chr5.145725410-145725459, MAX.chr5.178957564-178957598,         MAX.chr5.77268672-77268725, MPZ, NKX2-6, PRKCB, RBFOX3_B, SALL3,         and VSTM2B_A (see, Table 2, Example I).

From these 327 novel DNA methylation markers, further experiments identified the following markers and/or panels of markers capable of distinguishing ductal carcinoma in situ high grade (DCIS-HG) breast cancer tissue from ductal carcinoma in situ low grade (DCIS-LG) breast tissue:

-   -   SCRT2_B, MPZ, MAX.chr8.124173030-124173395, ITPRIPL1, ITPRIPL1,         DLX4, CALN1_A, and IGF2BP3_B (see, Table 15, Example I);     -   SCRT2_B, ITPRIPL1, and MAX.chr8.124173030-12417339 (100%         sensitive at 91% specificity) (see, Table 15, Example I),     -   DSCR6, SCRT2_B, MPZ, MAX.chr8.124173030-124173395, OSR2_A,         MAX.chr11.68622869-68622968, ITPRIPL1,         MAX.chr5.145725410-145725459, BHLHE23_C, and ITPRIPL1 (see,         Table 17, Example II).

As described herein, the technology provides a number of methylated DNA markers and subsets thereof (e.g., sets of 2, 3, 4, 5, 6, 7, or 8 markers) with high discrimination for various types of breast cancer (e.g., triple negative breast cancer, HER2⁺ breast cancer, Luminal A breast cancer, Luminal B breast cancer, BRCA1 breast cancer, BRCA2 breast cancer). Experiments applied a selection filter to candidate markers to identify markers that provide a high signal to noise ratio and a low background level to provide high specificity for purposes of breast cancer screening or diagnosis.

In some embodiments, the technology is related to assessing the presence of and methylation state of one or more of the markers identified herein in a biological sample (e.g., breast tissue, plasma sample). These markers comprise one or more differentially methylated regions (DMR) as discussed herein, e.g., as provided in Table 2. Methylation state is assessed in embodiments of the technology. As such, the technology provided herein is not restricted in the method by which a gene's methylation state is measured. For example, in some embodiments the methylation state is measured by a genome scanning method. For example, one method involves restriction landmark genomic scanning (Kawai et al. (1994) Mol. Cell. Biol. 14: 7421-7427) and another example involves methylation-sensitive arbitrarily primed PCR (Gonzalgo et al. (1997) Cancer Res. 57: 594-599). In some embodiments, changes in methylation patterns at specific CpG sites are monitored by digestion of genomic DNA with methylation-sensitive restriction enzymes followed by Southern analysis of the regions of interest (digestion-Southern method). In some embodiments, analyzing changes in methylation patterns involves a PCR-based process that involves digestion of genomic DNA with methylation-sensitive restriction enzymes or methylation-dependent restriction enzymes prior to PCR amplification (Singer-Sam et al. (1990) Nucl. Acids Res. 18: 687). In addition, other techniques have been reported that utilize bisulfite treatment of DNA as a starting point for methylation analysis. These include methylation-specific PCR (MSP) (Herman et al. (1992) Proc. Nal. Acad. Sci. USA 93: 9821-9826) and restriction enzyme digestion of PCR products amplified from bisulfite-converted DNA (Sadri and Hornsby (1996) Nucl. Acids Res. 24: 5058-5059; and Xiong and Laird (1997) Nucl. Acids Res. 25: 2532-2534). PCR techniques have been developed for detection of gene mutations (Kuppuswamy et al. (1991) Proc. Nal. Acad. Sci. USA 88: 1143-1147) and quantification of allelic-specific expression (Szabo and Mann (1995) Genes Dev. 9: 3097-3108; and Singer-Sam et al. (1992) PCR Methods Appl. 1: 160-163). Such techniques use internal primers, which anneal to a PCR-generated template and terminate immediately 5′ of the single nucleotide to be assayed. Methods using a “quantitative Ms-SNuPE assay” as described in U.S. Pat. No. 7,037,650 are used in some embodiments.

Upon evaluating a methylation state, the methylation state is often expressed as the fraction or percentage of individual strands of DNA that is methylated at a particular site (e.g., at a single nucleotide, at a particular region or locus, at a longer sequence of interest, e.g., up to a ˜100-bp, 200-bp, 500-bp, 1000-bp subsequence of a DNA or longer) relative to the total population of DNA in the sample comprising that particular site. Traditionally, the amount of the unmethylated nucleic acid is determined by PCR using calibrators. Then, a known amount of DNA is bisulfite treated and the resulting methylation-specific sequence is determined using either a real-time PCR or other exponential amplification, e.g., a QuARTS assay (e.g., as provided by U.S. Pat. No. 8,361,720; and U.S. Pat. Appl. Pub. Nos. 2012/0122088 and 2012/0122106, incorporated herein by reference).

For example, in some embodiments methods comprise generating a standard curve for the unmethylated target by using external standards. The standard curve is constructed from at least two points and relates the real-time Ct value for unmethylated DNA to known quantitative standards. Then, a second standard curve for the methylated target is constructed from at least two points and external standards. This second standard curve relates the Ct for methylated DNA to known quantitative standards. Next, the test sample Ct values are determined for the methylated and unmethylated populations and the genomic equivalents of DNA are calculated from the standard curves produced by the first two steps. The percentage of methylation at the site of interest is calculated from the amount of methylated DNAs relative to the total amount of DNAs in the population, e.g., (number of methylated DNAs)/(the number of methylated DNAs+number of unmethylated DNAs)×100.

Also provided herein are compositions and kits for practicing the methods. For example, in some embodiments, reagents (e.g., primers, probes) specific for one or more markers are provided alone or in sets (e.g., sets of primers pairs for amplifying a plurality of markers). Additional reagents for conducting a detection assay may also be provided (e.g., enzymes, buffers, positive and negative controls for conducting QuARTS, PCR, sequencing, bisulfite, or other assays). In some embodiments, the kits contain a reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent). In some embodiments, the kits containing one or more reagent necessary, sufficient, or useful for conducting a method are provided. Also provided are reactions mixtures containing the reagents. Further provided are master mix reagent sets containing a plurality of reagents that may be added to each other and/or to a test sample to complete a reaction mixture.

In some embodiments, the technology described herein is associated with a programmable machine designed to perform a sequence of arithmetic or logical operations as provided by the methods described herein. For example, some embodiments of the technology are associated with (e.g., implemented in) computer software and/or computer hardware. In one aspect, the technology relates to a computer comprising a form of memory, an element for performing arithmetic and logical operations, and a processing element (e.g., a microprocessor) for executing a series of instructions (e.g., a method as provided herein) to read, manipulate, and store data. In some embodiments, a microprocessor is part of a system for determining a methylation state (e.g., of one or more DMR, e.g., DMR 1-327 as provided in Table 2); comparing methylation states (e.g., of one or more DMR, e.g., DMR 1-327 as provided in Table 2); generating standard curves; determining a Ct value; calculating a fraction, frequency, or percentage of methylation (e.g., of one or more DMR, e.g., DMR 1-327 as provided in Table 2); identifying a CpG island; determining a specificity and/or sensitivity of an assay or marker; calculating an ROC curve and an associated AUC; sequence analysis; all as described herein or is known in the art.

In some embodiments, a microprocessor or computer uses methylation state data in an algorithm to predict a site of a cancer.

In some embodiments, a software or hardware component receives the results of multiple assays and determines a single value result to report to a user that indicates a cancer risk based on the results of the multiple assays (e.g., determining the methylation state of multiple DMR, e.g., as provided in Table 2). Related embodiments calculate a risk factor based on a mathematical combination (e.g., a weighted combination, a linear combination) of the results from multiple assays, e.g., determining the methylation states of multiple markers (such as multiple DMR, e.g., as provided in Table 2). In some embodiments, the methylation state of a DMR defines a dimension and may have values in a multidimensional space and the coordinate defined by the methylation states of multiple DMR is a result, e.g., to report to a user, e.g., related to a cancer risk.

Some embodiments comprise a storage medium and memory components. Memory components (e.g., volatile and/or nonvolatile memory) find use in storing instructions (e.g., an embodiment of a process as provided herein) and/or data (e.g., a work piece such as methylation measurements, sequences, and statistical descriptions associated therewith). Some embodiments relate to systems also comprising one or more of a CPU, a graphics card, and a user interface (e.g., comprising an output device such as display and an input device such as a keyboard).

Programmable machines associated with the technology comprise conventional extant technologies and technologies in development or yet to be developed (e.g., a quantum computer, a chemical computer, a DNA computer, an optical computer, a spintronics based computer, etc.).

In some embodiments, the technology comprises a wired (e.g., metallic cable, fiber optic) or wireless transmission medium for transmitting data. For example, some embodiments relate to data transmission over a network (e.g., a local area network (LAN), a wide area network (WAN), an ad-hoc network, the internet, etc.). In some embodiments, programmable machines are present on such a network as peers and in some embodiments the programmable machines have a client/server relationship.

In some embodiments, data are stored on a computer-readable storage medium such as a hard disk, flash memory, optical media, a floppy disk, etc.

In some embodiments, the technology provided herein is associated with a plurality of programmable devices that operate in concert to perform a method as described herein. For example, in some embodiments, a plurality of computers (e.g., connected by a network) may work in parallel to collect and process data, e.g., in an implementation of cluster computing or grid computing or some other distributed computer architecture that relies on complete computers (with onboard CPUs, storage, power supplies, network interfaces, etc.) connected to a network (private, public, or the internet) by a conventional network interface, such as Ethernet, fiber optic, or by a wireless network technology.

For example, some embodiments provide a computer that includes a computer-readable medium. The embodiment includes a random access memory (RAM) coupled to a processor. The processor executes computer-executable program instructions stored in memory. Such processors may include a microprocessor, an ASIC, a state machine, or other processor, and can be any of a number of computer processors, such as processors from Intel Corporation of Santa Clara, Calif. and Motorola Corporation of Schaumburg, Ill. Such processors include, or may be in communication with, media, for example computer-readable media, which stores instructions that, when executed by the processor, cause the processor to perform the steps described herein.

Embodiments of computer-readable media include, but are not limited to, an electronic, optical, magnetic, or other storage or transmission device capable of providing a processor with computer-readable instructions. Other examples of suitable media include, but are not limited to, a floppy disk, CD-ROM, DVD, magnetic disk, memory chip, ROM, RAM, an ASIC, a configured processor, all optical media, all magnetic tape or other magnetic media, or any other medium from which a computer processor can read instructions. Also, various other forms of computer-readable media may transmit or carry instructions to a computer, including a router, private or public network, or other transmission device or channel, both wired and wireless. The instructions may comprise code from any suitable computer-programming language, including, for example, C, C++, C#, Visual Basic, Java, Python, Perl, and JavaScript.

Computers are connected in some embodiments to a network. Computers may also include a number of external or internal devices such as a mouse, a CD-ROM, DVD, a keyboard, a display, or other input or output devices. Examples of computers are personal computers, digital assistants, personal digital assistants, cellular phones, mobile phones, smart phones, pagers, digital tablets, laptop computers, internet appliances, and other processor-based devices. In general, the computers related to aspects of the technology provided herein may be any type of processor-based platform that operates on any operating system, such as Microsoft Windows, Linux, UNIX, Mac OS X, etc., capable of supporting one or more programs comprising the technology provided herein. Some embodiments comprise a personal computer executing other application programs (e.g., applications). The applications can be contained in memory and can include, for example, a word processing application, a spreadsheet application, an email application, an instant messenger application, a presentation application, an Internet browser application, a calendar/organizer application, and any other application capable of being executed by a client device.

All such components, computers, and systems described herein as associated with the technology may be logical or virtual.

Accordingly, provided herein is technology related to a method of screening for breast cancer and/or various forms of breast cancer (e.g., triple negative breast cancer, HER2⁺ breast cancer, Luminal A breast cancer, Luminal B breast cancer, BRCA1 breast cancer, BRCA2 breast cancer) in a sample obtained from a subject, the method comprising assaying a methylation state of a marker in a sample obtained from a subject (e.g., breast tissue) (e.g., plasma sample) and identifying the subject as having breast cancer and/or a specific form of breast cancer when the methylation state of the marker is different than a methylation state of the marker assayed in a subject that does not have breast cancer, wherein the marker comprises a base in a differentially methylated region (DMR) selected from a group consisting of DMR 1-327 as provided in Table 2.

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has triple negative breast cancer: ABLIM1, AJAP1_B, ASCL2, ATP6V1B1, BANK1, CALN1_A, CALN1_B, CLIC6, DSCR6, FOXP4, GAD2, GCGR, GP5, GRASP, HBM, HNF1B_B, KLF16, MAGI2, MAX.chr11.14926602-14927148, MAX.chr12.4273906-4274012, MAX.chr17.73073682-73073814, MAX.chr18.76734362-76734370, MAX.chr2.97193478-97193562, MAX.chr22.42679578-42679917, MAX.chr4.8859253-8859329, MAX.chr4.8859602-8859669, MAX.chr4.8860002-8860038, MAX.chr5.145725410-145725459, MAX.chr6.157557371-157557657, MPZ, NKX2-6, PDX1, PLXNC1_A, PPARG, PRKCB, PTPRN2, RBFOX_A, SCRT2_A, SLC7A4, STAC2_B, STX16_A, STX16_B, TBX1, TRH_A, VSTM2B_A, ZBTB16, ZNF132, and ZSCAN23 (see, Table 3, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has triple negative breast cancer: CALN1_A, LOC100132891, NACAD, TRIM67, ATP6V1B1, DLX4, GP5, ITPRIPL1, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, PRKCB, ST8SIA4, STX16_B ITPRIPL1, KLF16, MAX.chr12.4273906-4274012, KCNK9, SCRT2_B, CDH4_E, HNF1B_B, TRH_A, MAX.chr20.1784209-1784461, MAX.chr12.4273906-4274012, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, and DSCR6 (see, Table 11, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has triple negative breast cancer: ATP6V1B1, MAX.chr11.14926602-14927148, PRKCB, TRH_A, MPZ, GP5, TRIM67, MAX.chr12.4273906-4274012, CALN1_A, MAX.chr12.4273906-4274012, MAX.chr5.42994866-42994936, SCRT2_B, MAX.chr5.145725410-145725459, BHLHE23_D, MAX.chr5.77268672-77268725, EMX1_A, DSCR6, and DLX4 (see, Table 16A, Example II).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has HER2⁺ breast cancer: ABLIM1, AFAP1L1, AKR1B1, ALOX5, AMN, ARL5C, BANK1, BCAT1, BEGAIN, BEST4, BHLHE23_B, BHLHE23_C, C17orf64, C1QL2, C7orf52, CALN1_B, CAV2, CD8A, CDH4_A, CDH4_B, CDH4_C, CDH4_D, CDH4_E, CDH4_F, CHST2_B, CLIP4, CR1, DLK1, DNAJC6, DNM3_A, EMX1_A, ESPN, FABP5, FAM150A, FLJ42875, GLP1R, GNG4, GYPC_A, HAND2, HES5, HNF1B_A, HNF1B_B, HOXA1_A, HOXA1_B, HOXA7_A, HOXA7_B, HOXA7_C, HOXD9, IGF2BP3_A, IGF2BP3_B, IGSF9B_A, IL15RA, INSM1, ITPKA_B, ITPRIPL1, KCNE3, KCNK17_B, LIME1, LOC100132891, LOC283999, LY6H, MAST1, MAX.chr1.158083198-158083476, MAX.chr1.228074764-228074977, MAX.chr1.46913931-46913950, MAX.chr10.130085265-130085312, MAX.chr11.68622869-68622968, MAX.chr14.101176106-101176260, MAX.chr15.96889069-96889128, MAX.chr17.8230197-8230314, MAX.chr19.46379903-46380197, MAX.chr2.97193163-97193287, MAX.chr2.97193478-97193562, MAX.chr20.1784209-1784461, MAX.chr21.44782441-44782498, MAX.chr22.23908718-23908782, MAX.chr5.145725410-145725459, MAX.chr5.178957564-178957598, MAX.chr5.180101084-180101094, MAX.chr5.42952185-42952280, MAX.chr5.42994866-42994936, MAX.chr6.27064703-27064783, MAX.chr7.152622607-152622638, MAX.chr8.145104132-145104218, MAX.chr9.136474504-136474527, MCF2L2, MSX2P1, NACAD, NID2_B, NID2_C, ODC1, OSR2_B, PAQR6, PCDH8, PIF1, PPARA, PPP2R5C, PRDM13_A, PRHOXNB, PRKCB, RBFOX3_A, RBFOX3_B, RFX8, SNCA, STAC2_A, STAC2_B, STX16_B SYT5, TIMP2, TMEFF2, TNFRSF10D, TRH_B, TRIM67, TRIM71_C, USP44_A, USP44_B, UTF1, UTS2R, VSTM2B_A, VSTM2B_B, ZFP64, and ZNF132 (see, Table 4, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has HER2⁺ breast cancer: BHLHE23_C, CALN1_A, CD1D, CHST2_A, FMN2, HOXA1_A, HOXA7_A, KCNH8, LOC100132891, MAX.chr15.96889013-96889128, NACAD, TRIM67, ATP6V1B1, C17orf64, CHST2_B, DLX4, DNM3_A, EMX1_A, IGF2BP3_A, IGF2BP3_B, ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, ODC1, PLXNC1_A, PRKCB, LOC100132891, ITPRIPL1, ABLIM1, MAX.chr12.4273906-4274012, MAX.chr19.46379903-46380197, ZSCAN12, BHLHE23_D, COL23A1, KCNK9, LAYN, PLXNC1_A, RIC3, SCRT2_B, ALOX5, CDH4_E, HNF1B_B, TRH_A, MAST1, ASCL2, MAX.chr20.1784209-1784461, RBFOX_A, MAX.chr12.4273906-4274012, GAS7, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, GYPC_B, DLX6, FBN1, OSR2_A, BEST4, AJAP1_B, DSCR6, and MAX.chr11.68622869-68622968 (see, Table 11, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has HER2⁺ breast cancer: ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, GP5, DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197, ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, CHST2_B, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, ABLIM1, BHLHE23_D, ZSCAN12, GRASP, C10orf125 (see, Table 16B, Example II).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has Luminal A breast cancer: ARL5C, BHLHE23_C, BMP6, C10orf125, C17orf64, C19orf66, CAMKV, CD1D, CDH4_E, CDH4_F, CHST2_A, CRHBP, DLX6, DNM3_A, DNM3_B, DNM3_C, ESYT3, ETS1_A, ETS1_B, FAM126A, FAM189A1, FAM20A, FAM59B, FBN1, FLRT2, FMN2, FOXP4, GAS7, GYPC_A, GYPC_B, HAND2, HES5, HMGA2, HNF1B_B, IGF2BP3_A, IGF2BP3_B, KCNH8, KCNK17_A, KCNQ2, KLHDC7B, LOC100132891, MAX.chr1.46913931-46913950, MAX.chr11.68622869-68622968, MAX.chr12.4273906-4274012, MAX.chr12.59990591-59990895, MAX.chr17.73073682-73073814, MAX.chr20.1783841-1784054, MAX.chr21.47063802-47063851, MAX.chr4.8860002-8860038, MAX.chr5.172234248-172234494, MAX.chr5.178957564-178957598, MAX.chr6.130686865-130686985, MAX.chr8.687688-687736, MAX.chr8.688863-688924, MAX.chr9.114010-114207, MPZ, NID2_A, NKX2-6, ODC1, OSR2_A, POU4F1, PRDM13_B, PRKCB, RASGRF2, RIPPLY2, SLC30A10, ST8SIA4, SYN2, TRIM71_A, TRIM71_B, TRIM71_C, UBTF, ULBP1, USP44_B, and VSTM2B_A (see, Table 5, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has Luminal A breast cancer: BHLHE23_C, CD1D, CHST2_A, FAM126A, FMN2, HOXA1_A, HOXA7_A, KCNH8, LOC100132891, MAX.chr15.96889013-96889128, SLC30A10, TRIM67, ATP6V1B1, BANK1, C10orf125, C17orf64, CHST2_B, DNM3_A, EMX1_A, GP5, IGF2BP3_A, IGF2BP3_B, ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, ODC1, PLXNC1_A, PRKCB, ST8SIA4, STX16_B UBTF, LOC100132891, ITPRIPL1, MAX.chr12.4273906-4274012, MAX.chr12.59990671-59990859, BHLHE23_D, COL23A1, KCNK9, OTX1, PLXNC1_A, HNF1B_B, MAST1, ASCL2, MAX.chr20.1784209-1784461, RBFOX_A, MAX.chr12.4273906-4274012, GAS7, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, GYPC_B, DLX6, FBN1, OSR2_A, BEST4, DSCR6, MAX.chr11.68622869-68622968 (see, Table 11, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has Luminal A breast cancer: ATP6V1B1, LMX1B_A, BANK1, OTX1, ST8SIA4, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, ALOX5, MAX.chr19.46379903-46380197, ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, CHST2_B, ITPRIPL1, IGF2BP3_B, CDH4_E, ABLIM1, SLC30A10, C10orf125 (see, Table 16C, Example II).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has Luminal B breast cancer: ACCN1, AJAP1_A, AJAP1_B, BEST4, CALN1_B, CBLN1_B, CDH4_E, DLX4, FOXP4, IGSF9B_B, ITPRIPL1, KCNA1, KLF16, LMX1B_A, MAST1, MAX.chr11.14926602-14927148, MAX.chr17.73073682-73073814, MAX.chr18.76734362-76734370, MAX.chr18.76734423-76734476, MAX.chr19.30719261-30719354, MAX.chr22.42679578-42679917, MAX.chr4.8860002-8860038, MAX.chr5.145725410-145725459, MAX.chr5.178957564-178957598, MAX.chr5.77268672-77268725, MAX.chr8.124173128-124173268, MPZ, PPARA, PRMT1, RBFOX3_B, RYR2_A, SALL3, SCRT2_A, SPHK2, STX16_B SYNJ2, TMEM176A, TSHZ3, and VIPR2 (see, Table 6, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has Luminal B breast cancer: CALN1_A, LOC100132891, MAX.chr15.96889013-96889128, ATP6V1B1, C17orf64, DLX4, ITPRIPL1, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, PRKCB, ITPRIPL1, KLF16, MAX.chr12.4273906-4274012, MAX.chr19.46379903-46380197, BHLHE23_D, HNF1B_B, TRH_A, ASCL2, MAX.chr20.1784209-1784461, MAX.chr12.4273906-4274012, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, BEST4, AJAP1_B, and DSCR6 (see, Table 11, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has Luminal B breast cancer: ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197, CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1, IGF2BP3_B, CDH4_E, DLX4, ABLIM1, BHLHE23_D (see, Table 16D, Example II).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has BRCA1 breast cancer: C10orf93, C20orf195_A, C20orf195_B, CALN1_B, CBLN1_A, CBLN1_B, CCDC61, CCND2_A, CCND2_B, CCND2_C, EMX1_B, FAM150B, GRASP, HBM, ITPRIPL1, KCNK17_A, KIAA1949, LOC100131176, MAST1, MAX.chr1.8277285-8277316, MAX.chr1.8277479-8277527, MAX.chr11.14926602-14926729, MAX.chr11.14926860-14927148, MAX.chr15.96889013-96889128, MAX.chr18.5629721-5629791, MAX.chr19.30719261-30719354, MAX.chr22.42679767-42679917, MAX.chr5.178957564-178957598, MAX.chr5.77268672-77268725, MAX.chr6.157556793-157556856, MAX.chr8.124173030-124173395, MN1, MPZ, NR2F6, PDXK_A, PDXK_B, PTPRM, RYR2_B, SERPINB9_A, SERPINB9_B, SLC8A3, STX16_B TEPP, TOX, VIPR2, VSTM2B_A, ZNF486, ZNF626, and ZNF671 (see, Table 7, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has BRCA1 breast cancer: BHLHE23_C, CALN1_A, CD1D, HOXA7_A, LOC100132891, MAX.chr1.8277479-8277527, MAX.chr15.96889013-96889128, NACAD, ATP6V1B1, BANK1, C17orf64, DLX4, EMX1_A, FOXP4, GP5, ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, PRKCB, STX16_B UBTF, LOC100132891, ITPRIPL1, ABLIM1, MAX.chr19.46379903-46380197, ZSCAN12, BHLHE23_D, CXCL12, KCNK9, OTX1, RIC3, SCRT2_B, MAX.chr17.73073682-73073814, CDH4_E, HNF1B_B, TRH_A, MAX.chr20.1784209-1784461, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, BEST4, and DSCR6 (see, Table 11, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has BRCA2 breast cancer: ANTXR2, B3GNT5, BHLHE23_C, BMP4, CHRNA7, EPHA4, FAM171A1, FAM20A, FMNL2, FSCN1, GSTP1, HBM, IGFBP5, IL17REL, ITGA9, ITPRIPL1, KIRREL2, LRRC34, MAX.chr1.239549742-239549886, MAX.chr1.8277479-8277527, MAX.chr11.14926602-14926729, MAX.chr11.14926860-14927148, MAX.chr15.96889013-96889128, MAX.chr2.238864674-238864735, MAX.chr5.81148300-81148332, MAX.chr7.151145632-151145743, MAX.chr8.124173030-124173395, MAX.chr8.143533298-143533558, MERTK, MPZ, NID2_C, NTRK3, OLIG3_A, OLIG3_B, OSR2_C, PROM1, RGS17, SBNO2, STX16_B TBKBP1, TLX1NB, VIPR2, VN1R2, VSNL1, and ZFP64 (see, Table 8, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has BRCA2 breast cancer: MAX.chr15.96889013-96889128, ATP6V1B1, C17orf64, ITPRIPL1, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, LOC100132891, ITPRIPL1, ABLIM1, MAX.chr19.46379903-46380197, COL23A1, LAYN, OTX1, TRH_A, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968 (see, Table 11, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer indicates the subject has invasive breast cancer: CDH4_E, FLJ42875, GAD2, GRASP, ITPRIPL1, KCNA1, MAX.chr12.4273906-4274012, MAX.chr18.76734362-76734370, MAX.chr18.76734423-76734476, MAX.chr19.30719261-30719354, MAX.chr4.8859602-8859669, MAX.chr4.8860002-8860038, MAX.chr5.145725410-145725459, MAX.chr5.178957564-178957598, MAX.chr5.77268672-77268725, MPZ, NKX2-6, PRKCB, RBFOX3_B, SALL3, and VSTM2B_A (see, Table 9, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer distinguishes between ductal carcinoma in situ high grade (DCIS-HG) breast cancer tissue from ductal carcinoma in situ low grade (DCIS-LG) breast tissue: SCRT2_B, MPZ, MAX.chr8.124173030-124173395, ITPRIPL1, ITPRIPL1, DLX4, CALN1_A, and IGF2BP3_B (see, Table 15, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer distinguishes between ductal carcinoma in situ high grade (DCIS-HG) breast cancer tissue from ductal carcinoma in situ low grade (DCIS-LG) breast tissue: SCRT2_B, ITPRIPL1, and MAX.chr8.124173030-12417339 (100% sensitive at 91% specificity) (see, Table 15, Example I).

In some embodiments wherein the sample obtained from the subject is breast tissue and the methylation state of one or more of the following markers is different than a methylation state of the one or more markers assayed in a subject that does not have breast cancer distinguishes between ductal carcinoma in situ high grade (DCIS-HG) breast cancer tissue from ductal carcinoma in situ low grade (DCIS-LG) breast tissue: DSCR6, SCRT2_B, MPZ, MAX.chr8.124173030-124173395, OSR2_A, MAX.chr11.68622869-68622968, ITPRIPL1, MAX.chr5.145725410-145725459, BHLHE23_C, and ITPRIPL1 (see, Table 17, Example II).

The technology is related to identifying and discriminating breast cancer and/or various forms of breast cancer (e.g., triple negative breast cancer, HER2⁺ breast cancer, Luminal A breast cancer, Luminal B breast cancer, BRCA1 breast cancer, BRCA2 breast cancer). Some embodiments provide methods comprising assaying a plurality of markers, e.g., comprising assaying 2 to 11 to 100 or 120 or 327 markers.

The technology is not limited in the methylation state assessed. In some embodiments assessing the methylation state of the marker in the sample comprises determining the methylation state of one base. In some embodiments, assaying the methylation state of the marker in the sample comprises determining the extent of methylation at a plurality of bases. Moreover, in some embodiments the methylation state of the marker comprises an increased methylation of the marker relative to a normal methylation state of the marker. In some embodiments, the methylation state of the marker comprises a decreased methylation of the marker relative to a normal methylation state of the marker. In some embodiments the methylation state of the marker comprises a different pattern of methylation of the marker relative to a normal methylation state of the marker.

Furthermore, in some embodiments the marker is a region of 100 or fewer bases, the marker is a region of 500 or fewer bases, the marker is a region of 1000 or fewer bases, the marker is a region of 5000 or fewer bases, or, in some embodiments, the marker is one base. In some embodiments the marker is in a high CpG density promoter.

The technology is not limited by sample type. For example, in some embodiments the sample is a stool sample, a tissue sample (e.g., breast tissue sample), a blood sample (e.g., plasma, serum, whole blood), an excretion, or a urine sample.

Furthermore, the technology is not limited in the method used to determine methylation state. In some embodiments the assaying comprises using methylation specific polymerase chain reaction, nucleic acid sequencing, mass spectrometry, methylation specific nuclease, mass-based separation, or target capture. In some embodiments, the assaying comprises use of a methylation specific oligonucleotide. In some embodiments, the technology uses massively parallel sequencing (e.g., next-generation sequencing) to determine methylation state, e.g., sequencing-by-synthesis, real-time (e.g., single-molecule) sequencing, bead emulsion sequencing, nanopore sequencing, etc.

The technology provides reagents for detecting a DMR, e.g., in some embodiments are provided a set of oligonucleotides comprising the sequences provided by SEQ ID NO: 1-254 (see, Table 10). In some embodiments are provided an oligonucleotide comprising a sequence complementary to a chromosomal region having a base in a DMR, e.g., an oligonucleotide sensitive to methylation state of a DMR.

The technology provides various panels of markers use for identifying triple negative breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is ABLIM1, AJAP1_B, ASCL2, ATP6V1B1, BANK1, CALN1_A, CALN1_B, CLIC6, DSCR6, FOXP4, GAD2, GCGR, GP5, GRASP, HBM, HNF1B_B, KLF16, MAGI2, MAX.chr11.14926602-14927148, MAX.chr12.4273906-4274012, MAX.chr17.73073682-73073814, MAX.chr18.76734362-76734370, MAX.chr2.97193478-97193562, MAX.chr22.42679578-42679917, MAX.chr4.8859253-8859329, MAX.chr4.8859602-8859669, MAX.chr4.8860002-8860038, MAX.chr5.145725410-145725459, MAX.chr6.157557371-157557657, MPZ, NKX2-6, PDX1, PLXNC1_A, PPARG, PRKCB, PTPRN2, RBFOX_A, SCRT2_A, SLC7A4, STAC2_B, STX16_A, STX16_B, TBX1, TRH_A, VSTM2B_A, ZBTB16, ZNF132, and ZSCAN23 (see, Table 3, Example I).

The technology provides various panels of markers use for identifying triple negative breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is CALN1_A, LOC100132891, NACAD, TRIM67, ATP6V1B1, DLX4, GP5, ITPRIPL1, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, PRKCB, ST8SIA4, STX16_B ITPRIPL1, KLF16, MAX.chr12.4273906-4274012, KCNK9, SCRT2_B, CDH4_E, HNF1B_B, TRH_A, MAX.chr20.1784209-1784461, MAX.chr12.4273906-4274012, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, and DSCR6 (see, Table 11, Example I).

The technology provides various panels of markers use for identifying triple negative breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is ATP6V1B1, MAX.chr11.14926602-14927148, PRKCB, TRH_A, MPZ, GP5, TRIM67, MAX.chr12.4273906-4274012, CALN1_A, MAX.chr12.4273906-4274012, MAX.chr5.42994866-42994936, SCRT2_B, MAX.chr5.145725410-145725459, BHLHE23_D, MAX.chr5.77268672-77268725, EMX1_A, DSCR6, and DLX4 (see, Table 16A, Example II).

The technology provides various panels of markers use for identifying HER2⁺ breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is ABLIM1, AFAP1L1, AKR1B1, ALOX5, AMN, ARL5C, BANK1, BCAT1, BEGAIN, BEST4, BHLHE23_B, BHLHE23_C, C17orf64, C1QL2, C7orf52, CALN1_B, CAV2, CD8A, CDH4_A, CDH4_B, CDH4_C, CDH4_D, CDH4_E, CDH4_F, CHST2_B, CLIP4, CR1, DLK1, DNAJC6, DNM3_A, EMX1_A, ESPN, FABP5, FAM150A, FLJ42875, GLP1R, GNG4, GYPC_A, HAND2, HES5, HNF1B_A, HNF1B_B, HOXA1_A, HOXA1_B, HOXA7_A, HOXA7_B, HOXA7_C, HOXD9, IGF2BP3_A, IGF2BP3_B, IGSF9B_A, IL15RA, INSM1, ITPKA_B, ITPRIPL1, KCNE3, KCNK17_B, LIME1, LOC100132891, LOC283999, LY6H, MAST1, MAX.chr1.158083198-158083476, MAX.chr1.228074764-228074977, MAX.chr1.46913931-46913950, MAX.chr10.130085265-130085312, MAX.chr11.68622869-68622968, MAX.chr14.101176106-101176260, MAX.chr15.96889069-96889128, MAX.chr17.8230197-8230314, MAX.chr19.46379903-46380197, MAX.chr2.97193163-97193287, MAX.chr2.97193478-97193562, MAX.chr20.1784209-1784461, MAX.chr21.44782441-44782498, MAX.chr22.23908718-23908782, MAX.chr5.145725410-145725459, MAX.chr5.178957564-178957598, MAX.chr5.180101084-180101094, MAX.chr5.42952185-42952280, MAX.chr5.42994866-42994936, MAX.chr6.27064703-27064783, MAX.chr7.152622607-152622638, MAX.chr8.145104132-145104218, MAX.chr9.136474504-136474527, MCF2L2, MSX2P1, NACAD, NID2_B, NID2_C, ODC1, OSR2_B, PAQR6, PCDH8, PIF1, PPARA, PPP2R5C, PRDM13_A, PRHOXNB, PRKCB, RBFOX3_A, RBFOX3_B, RFX8, SNCA, STAC2_A, STAC2_B, STX16_B SYT5, TIMP2, TMEFF2, TNFRSF10D, TRH_B, TRIM67, TRIM71_C, USP44_A, USP44_B, UTF1, UTS2R, VSTM2B_A, VSTM2B_B, ZFP64, and ZNF132 (see, Table 4, Example I).

The technology provides various panels of markers use for identifying HER2⁺ breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is BHLHE23_C, CALN1_A, CD1D, CHST2_A, FMN2, HOXA1_A, HOXA7_A, KCNH8, LOC100132891, MAX.chr15.96889013-96889128, NACAD, TRIM67, ATP6V1B1, C17orf64, CHST2_B, DLX4, DNM3_A, EMX1_A, IGF2BP3_A, IGF2BP3_B, ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, ODC1, PLXNC1_A, PRKCB, LOC100132891, ITPRIPL1, ABLIM1, MAX.chr12.4273906-4274012, MAX.chr19.46379903-46380197, ZSCAN12, BHLHE23_D, COL23A1, KCNK9, LAYN, PLXNC1_A, RIC3, SCRT2_B, ALOX5, CDH4_E, HNF1B_B, TRH_A, MAST1, ASCL2, MAX.chr20.1784209-1784461, RBFOX_A, MAX.chr12.4273906-4274012, GAS7, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, GYPC_B, DLX6, FBN1, OSR2_A, BEST4, AJAP1_B, DSCR6, and MAX.chr11.68622869-68622968 (see, Table 11, Example I).

The technology provides various panels of markers use for identifying HER2⁺ breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, GP5, DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197, ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, CHST2_B, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, ABLIM1, BHLHE23_D, ZSCAN12, GRASP, C10orf25 (see, Table 16B, Example II).

The technology provides various panels of markers use for identifying Luminal A breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is ARL5C, BHLHE23_C, BMP6, C10orf125, C17orf64, C19orf66, CAMKV, CD1D, CDH4_E, CDH4_F, CHST2_A, CRHBP, DLX6, DNM3_A, DNM3_B, DNM3_C, ESYT3, ETS1_A, ETS1_B, FAM126A, FAM189A1, FAM20A, FAM59B, FBN1, FLRT2, FMN2, FOXP4, GAS7, GYPC_A, GYPC_B, HAND2, HES5, HMGA2, HNF1B_B, IGF2BP3_A, IGF2BP3_B, KCNH8, KCNK17_A, KCNQ2, KLHDC7B, LOC100132891, MAX.chr1.46913931-46913950, MAX.chr11.68622869-68622968, MAX.chr12.4273906-4274012, MAX.chr12.59990591-59990895, MAX.chr17.73073682-73073814, MAX.chr20.1783841-1784054, MAX.chr21.47063802-47063851, MAX.chr4.8860002-8860038, MAX.chr5.172234248-172234494, MAX.chr5.178957564-178957598, MAX.chr6.130686865-130686985, MAX.chr8.687688-687736, MAX.chr8.688863-688924, MAX.chr9.114010-114207, MPZ, NID2_A, NKX2-6, ODC1, OSR2_A, POU4F1, PRDM13_B, PRKCB, RASGRF2, RIPPLY2, SLC30A10, ST8SIA4, SYN2, TRIM71_A, TRIM71_B, TRIM71_C, UBTF, ULBP1, USP44_B, and VSTM2B_A (see, Table 5, Example I).

The technology provides various panels of markers use for identifying Luminal A breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is BHLHE23_C, CD1D, CHST2_A, FAM126A, FMN2, HOXA1_A, HOXA7_A, KCNH8, LOC100132891, MAX.chr15.96889013-96889128, SLC30A10, TRIM67, ATP6V1B1, BANK, C10orf125, C17orf64, CHST2_B, DNM3_A, EMX1_A, GP5, IGF2BP3_A, IGF2BP3_B, ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, ODC1, PLXNC1_A, PRKCB, ST8SIA4, STX16_B UBTF, LOC100132891, ITPRIPL1, MAX.chr12.4273906-4274012, MAX.chr12.59990671-59990859, BHLHE23_D, COL23A1, KCNK9, OTX1, PLXNC1_A, HNF1B_B, MAST1, ASCL2, MAX.chr20.1784209-1784461, RBFOX_A, MAX.chr12.4273906-4274012, GAS7, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, GYPC_B, DLX6, FBN1, OSR2_A, BEST4, DSCR6, MAX.chr11.68622869-68622968 (see, Table 11, Example I).

The technology provides various panels of markers use for identifying Luminal A breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is ATP6V1B1, LMX1B_A, BANK1, OTX1, ST8SIA4, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, ALOX5, MAX.chr19.46379903-46380197, ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, CHST2_B, ITPRIPL1, IGF2BP3_B, CDH4_E, ABLIM1, SLC30A10, C10orf125 (see, Table 16C, Example II).

The technology provides various panels of markers use for identifying Luminal B breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is ACCN1, AJAP1_A, AJAP1_B, BEST4, CALN1_B, CBLN1_B, CDH4_E, DLX4, FOXP4, IGSF9B_B, ITPRIPL1, KCNA1, KLF16, LMX1B_A, MAST1, MAX.chr11.14926602-14927148, MAX.chr17.73073682-73073814, MAX.chr18.76734362-76734370, MAX.chr18.76734423-76734476, MAX.chr19.30719261-30719354, MAX.chr22.42679578-42679917, MAX.chr4.8860002-8860038, MAX.chr5.145725410-145725459, MAX.chr5.178957564-178957598, MAX.chr5.77268672-77268725, MAX.chr8.124173128-124173268, MPZ, PPARA, PRMT1, RBFOX3_B, RYR2_A, SALL3, SCRT2_A, SPHK2, STX16_B SYNJ2, TMEM176A, TSHZ3, and VIPR2 (see, Table 6, Example I).

The technology provides various panels of markers use for identifying Luminal B breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is CALN1_A, LOC100132891, MAX.chr15.96889013-96889128, ATP6V1B1, C17orf64, DLX4, ITPRIPL1, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, PRKCB, ITPRIPL1, KLF16, MAX.chr12.4273906-4274012, MAX.chr19.46379903-46380197, BHLHE23_D, HNF1B_B, TRH_A, ASCL2, MAX.chr20.1784209-1784461, MAX.chr12.4273906-4274012, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, BEST4, AJAP1_B, and DSCR6 (see, Table 11, Example I).

The technology provides various panels of markers use for identifying Luminal B breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197, CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1, IGF2BP3_B, CDH4_E, DLX4, ABLIM1, BHLHE23_D (see, Table 16D, Example II).

The technology provides various panels of markers use for identifying BRCA1 breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is C10orf93, C20orf195_A, C20orf195_B, CALN1_B, CBLN1_A, CBLN1_B, CCDC61, CCND2_A, CCND2_B, CCND2_C, EMX1_B, FAM150B, GRASP, HBM, ITPRIPL1, KCNK17_A, KIAA1949, LOC100131176, MAST1, MAX.chr1.8277285-8277316, MAX.chr1.8277479-8277527, MAX.chr11.14926602-14926729, MAX.chr11.14926860-14927148, MAX.chr15.96889013-96889128, MAX.chr18.5629721-5629791, MAX.chr19.30719261-30719354, MAX.chr22.42679767-42679917, MAX.chr5.178957564-178957598, MAX.chr5.77268672-77268725, MAX.chr6.157556793-157556856, MAX.chr8.124173030-124173395, MN1, MPZ, NR2F6, PDXK_A, PDXK_B, PTPRM, RYR2_B, SERPINB9_A, SERPINB9_B, SLC8A3, STX16_B TEPP, TOX, VIPR2, VSTM2B_A, ZNF486, ZNF626, and ZNF671 (see, Table 7, Example I).

The technology provides various panels of markers use for identifying BRCA1 breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is BHLHE23_C, CALN1_A, CD1D, HOXA7_A, LOC100132891, MAX.chr1.8277479-8277527, MAX.chr15.96889013-96889128, NACAD, ATP6V1B1, BANK1, C17orf64, DLX4, EMX1_A, FOXP4, GP5, ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, PRKCB, STX16_B UBTF, LOC100132891, ITPRIPL1, ABLIM1, MAX.chr19.46379903-46380197, ZSCAN12, BHLHE23_D, CXCL12, KCNK9, OTX1, RIC3, SCRT2_B, MAX.chr17.73073682-73073814, CDH4_E, HNF1B_B, TRH_A, MAX.chr20.1784209-1784461, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, BEST4, and DSCR6 (see, Table 11, Example I).

The technology provides various panels of markers use for identifying BRCA2 breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is ANTXR2, B3GNT5, BHLHE23_C, BMP4, CHRNA7, EPHA4, FAM171A1, FAM20A, FMNL2, FSCN1, GSTP1, HBM, IGFBP5, IL17REL, ITGA9, ITPRIPL1, KIRREL2, LRRC34, MAX.chr1.239549742-239549886, MAX.chr1.8277479-8277527, MAX.chr11.14926602-14926729, MAX.chr11.14926860-14927148, MAX.chr15.96889013-96889128, MAX.chr2.238864674-238864735, MAX.chr5.81148300-81148332, MAX.chr7.151145632-151145743, MAX.chr8.124173030-124173395, MAX.chr8.143533298-143533558, MERTK, MPZ, NID2_C, NTRK3, OLIG3_A, OLIG3_B, OSR2_C, PROM, RGS17, SBNO2, STX16_B TBKBP1, TLX1NB, VIPR2, VN1R2, VSNL1, and ZFP64 (see, Table 8, Example I).

The technology provides various panels of markers use for identifying BRCA2 breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is MAX.chr15.96889013-96889128, ATP6V1B1, C17orf64, ITPRIPL1, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, LOC100132891, ITPRIPL1, ABLIM1, MAX.chr19.46379903-46380197, COL23A1, LAYN, OTX1, TRH_A, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968 (see, Table 11, Example I).

The technology provides various panels of markers use for identifying invasive breast cancer, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is CDH4_E, FLJ42875, GAD2, GRASP, ITPRIPL1, KCNA1, MAX.chr12.4273906-4274012, MAX.chr18.76734362-76734370, MAX.chr18.76734423-76734476, MAX.chr19.30719261-30719354, MAX.chr4.8859602-8859669, MAX.chr4.8860002-8860038, MAX.chr5.145725410-145725459, MAX.chr5.178957564-178957598, MAX.chr5.77268672-77268725, MPZ, NKX2-6, PRKCB, RBFOX3_B, SALL3, and VSTM2B_A (see, Table 9, Example I).

The technology provides various panels of markers use for distinguishing between ductal carcinoma in situ high grade (DCIS-HG) breast cancer tissue from ductal carcinoma in situ low grade (DCIS-LG) breast tissue, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is SCRT2_B, MPZ, MAX.chr8.124173030-124173395, ITPRIPL1, ITPRIPL1, DLX4, CALN1_A, and IGF2BP3_B (see, Table 15, Example I).

The technology provides various panels of markers use for distinguishing between ductal carcinoma in situ high grade (DCIS-HG) breast cancer tissue from ductal carcinoma in situ low grade (DCIS-LG) breast tissue, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is SCRT2_B, ITPRIPL1, and MAX.chr8.124173030-12417339 (100% sensitive at 91% specificity) (see, Table 15, Example I).

The technology provides various panels of markers use for distinguishing between ductal carcinoma in situ high grade (DCIS-HG) breast cancer tissue from ductal carcinoma in situ low grade (DCIS-LG) breast tissue, e.g., in some embodiments the marker comprises a chromosomal region having an annotation that is DSCR6, SCRT2_B, MPZ, MAX.chr8.124173030-124173395, OSR2_A, MAX.chr11.68622869-68622968, ITPRIPL1, MAX.chr5.145725410-145725459, BHLHE23_C, and ITPRIPL1 (see, Table 17, Example II).

Kit embodiments are provided, e.g., a kit comprising a reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent); and a control nucleic acid comprising a sequence from a DMR selected from a group consisting of DMR 1-327 (from Table 2) and having a methylation state associated with a subject who does not have breast cancer. In some embodiments, kits comprise a bisulfite reagent and an oligonucleotide as described herein. In some embodiments, kits comprise a reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent); and a control nucleic acid comprising a sequence from a DMR selected from a group consisting of DMR 1-327 (from Table 2) and having a methylation state associated with a subject who has breast cancer. Some kit embodiments comprise a sample collector for obtaining a sample from a subject (e.g., a stool sample; breast tissue sample; plasma sample, serum sample, whole blood sample); reagents for isolating a nucleic acid from the sample; a reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent); and an oligonucleotide as described herein.

The technology is related to embodiments of compositions (e.g., reaction mixtures). In some embodiments are provided a composition comprising a nucleic acid comprising a DMR and a reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent). Some embodiments provide a composition comprising a nucleic acid comprising a DMR and an oligonucleotide as described herein. Some embodiments provide a composition comprising a nucleic acid comprising a DMR and a methylation-sensitive restriction enzyme. Some embodiments provide a composition comprising a nucleic acid comprising a DMR and a polymerase.

Additional related method embodiments are provided for screening for various forms of breast cancer (e.g., triple negative breast cancer, HER2⁺ breast cancer, Luminal A breast cancer, Luminal B breast cancer, BRCA1 breast cancer, BRCA2 breast cancer) in a sample obtained from a subject (e.g., breast tissue sample; plasma sample; stool sample), e.g., a method comprising determining a methylation state of a marker in the sample comprising a base in a DMR that is one or more of DMR 1-327 (from Table 2); comparing the methylation state of the marker from the subject sample to a methylation state of the marker from a normal control sample from a subject who does not have breast cancer (e.g., triple negative breast cancer, HER2⁺ breast cancer, Luminal A breast cancer, Luminal B breast cancer, BRCA1 breast cancer, BRCA2 breast cancer); and determining a confidence interval and/or a p value of the difference in the methylation state of the subject sample and the normal control sample. In some embodiments, the confidence interval is 90%, 95%, 97.5%, 98%, 99%, 99.5%, 99.9% or 99.99% and the p value is 0.1, 0.05, 0.025, 0.02, 0.01, 0.005, 0.001, or 0.0001. Some embodiments of methods provide steps of reacting a nucleic acid comprising a DMR with a reagent capable of modifying nucleic acid in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent) to produce, for example, nucleic acid modified in a methylation-specific manner; sequencing the nucleic acid modified in a methylation-specific manner to provide a nucleotide sequence of the nucleic acid modified in a methylation-specific manner; comparing the nucleotide sequence of the nucleic acid modified in a methylation-specific manner with a nucleotide sequence of a nucleic acid comprising the DMR from a subject who does not have breast cancer and/or a form of breast cancer to identify differences in the two sequences; and identifying the subject as having breast cancer (e.g., triple negative breast cancer, HER2⁺ breast cancer, Luminal A breast cancer, Luminal B breast cancer, BRCA1 breast cancer, BRCA2 breast cancer) when a difference is present.

Systems for screening for breast cancer in a sample obtained from a subject are provided by the technology. Exemplary embodiments of systems include, e.g., a system for screening for types of breast cancer (e.g., triple negative breast cancer, HER2⁺ breast cancer, Luminal A breast cancer, Luminal B breast cancer, BRCA1 breast cancer, BRCA2 breast cancer) in a sample obtained from a subject (e.g., breast tissue sample; plasma sample; stool sample), the system comprising an analysis component configured to determine the methylation state of a sample, a software component configured to compare the methylation state of the sample with a control sample or a reference sample methylation state recorded in a database, and an alert component configured to alert a user of a breast-cancer-associated methylation state. An alert is determined in some embodiments by a software component that receives the results from multiple assays (e.g., determining the methylation states of multiple markers, e.g., DMR, e.g., as provided in Table 2) and calculating a value or result to report based on the multiple results. Some embodiments provide a database of weighted parameters associated with each DMR provided herein for use in calculating a value or result and/or an alert to report to a user (e.g., such as a physician, nurse, clinician, etc.). In some embodiments all results from multiple assays are reported and in some embodiments one or more results are used to provide a score, value, or result based on a composite of one or more results from multiple assays that is indicative of a cancer risk in a subject.

In some embodiments of systems, a sample comprises a nucleic acid comprising a DMR. In some embodiments the system further comprises a component for isolating a nucleic acid, a component for collecting a sample such as a component for collecting a stool sample. In some embodiments, the system comprises nucleic acid sequences comprising a DMR. In some embodiments the database comprises nucleic acid sequences from subjects who do not have breast cancer and/or specific types of breast cancer (e.g., triple negative breast cancer, HER2⁺ breast cancer, Luminal A breast cancer, Luminal B breast cancer, BRCA1 breast cancer, BRCA2 breast cancer). Also provided are nucleic acids, e.g., a set of nucleic acids, each nucleic acid having a sequence comprising a DMR. In some embodiments the set of nucleic acids wherein each nucleic acid has a sequence from a subject who does not have breast cancer and/or specific types of breast cancer. Related system embodiments comprise a set of nucleic acids as described and a database of nucleic acid sequences associated with the set of nucleic acids. Some embodiments further comprise a reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent). And, some embodiments further comprise a nucleic acid sequencer.

In certain embodiments, methods for characterizing a sample (e.g., breast tissue sample; plasma sample; whole blood sample; serum sample; stool sample) from a human patient are provided. For example, in some embodiments such embodiments comprise obtaining DNA from a sample of a human patient; assaying a methylation state of a DNA methylation marker comprising a base in a differentially methylated region (DMR) selected from a group consisting of DMR 1-327 from Table 2; and comparing the assayed methylation state of the one or more DNA methylation markers with methylation level references for the one or more DNA methylation markers for human patients not having breast cancer and/or specific types of breast cancer (e.g., triple negative breast cancer, HER2⁺ breast cancer, Luminal A breast cancer, Luminal B breast cancer, BRCA1 breast cancer, BRCA2 breast cancer).

Such methods are not limited to a particular type of sample from a human patient. In some embodiments, the sample is a breast tissue sample. In some embodiments, the sample is a plasma sample. In some embodiments, the sample is a stool sample, a tissue sample, a breast tissue sample, a blood sample (e.g., plasma sample, whole blood sample, serum sample), or a urine sample.

In some embodiments, such methods comprise assaying a plurality of DNA methylation markers. In some embodiments, such methods comprise assaying 2 to 11 DNA methylation markers. In some embodiments, such methods comprise assaying 12 to 120 DNA methylation markers. In some embodiments, such methods comprise assaying 2 to 327 DNA methylation markers. In some embodiments, such methods comprise assaying the methylation state of the one or more DNA methylation markers in the sample comprises determining the methylation state of one base. In some embodiments, such methods comprise assaying the methylation state of the one or more DNA methylation markers in the sample comprises determining the extent of methylation at a plurality of bases. In some embodiments, such methods comprise assaying a methylation state of a forward strand or assaying a methylation state of a reverse strand.

In some embodiments, the DNA methylation marker is a region of 100 or fewer bases. In some embodiments, the DNA methylation marker is a region of 500 or fewer bases. In some embodiments, the DNA methylation marker is a region of 1000 or fewer bases. In some embodiments, the DNA methylation marker is a region of 5000 or fewer bases. In some embodiments, the DNA methylation marker is one base. In some embodiments, the DNA methylation marker is in a high CpG density promoter.

In some embodiments, the assaying comprises using methylation specific polymerase chain reaction, nucleic acid sequencing, mass spectrometry, methylation specific nuclease, mass-based separation, or target capture.

In some embodiments, the assaying comprises use of a methylation specific oligonucleotide. In some embodiments, the methylation specific oligonucleotide is selected from the group consisting of SEQ ID NO: 1-254 (Table 10).

In some embodiments, a chromosomal region having an annotation selected from the group consisting of ABLIM1, AJAP1_B, ASCL2, ATP6V1B1, BANK1, CALN1_A, CALN1_B, CLIC6, DSCR6, FOXP4, GAD2, GCGR, GP5, GRASP, HBM, HNF1B_B, KLF16, MAGI2, MAX.chr11.14926602-14927148, MAX.chr12.4273906-4274012, MAX.chr17.73073682-73073814, MAX.chr18.76734362-76734370, MAX.chr2.97193478-97193562, MAX.chr22.42679578-42679917, MAX.chr4.8859253-8859329, MAX.chr4.8859602-8859669, MAX.chr4.8860002-8860038, MAX.chr5.145725410-145725459, MAX.chr6.157557371-157557657, MPZ, NKX2-6, PDX1, PLXNC1_A, PPARG, PRKCB, PTPRN2, RBFOX_A, SCRT2_A, SLC7A4, STAC2_B, STX16_A, STX16_B, TBX1, TRH_A, VSTM2B_A, ZBTB16, ZNF132, and ZSCAN23 (see, Table 3, Example I) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of CALN1_A, LOC100132891, NACAD, TRIM67, ATP6V1B1, DLX4, GP5, ITPRIPL1, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, PRKCB, ST8SIA4, STX16_B ITPRIPL1, KLF16, MAX.chr12.4273906-4274012, KCNK9, SCRT2_B, CDH4_E, HNF1B_B, TRH_A, MAX.chr20.1784209-1784461, MAX.chr12.4273906-4274012, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, and DSCR6 (see, Table 11, Example I) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of ATP6V1B1, MAX.chr11.14926602-14927148, PRKCB, TRH_A, MPZ, GP5, TRIM67, MAX.chr12.4273906-4274012, CALN1_A, MAX.chr12.4273906-4274012, MAX.chr5.42994866-42994936, SCRT2_B, MAX.chr5.145725410-145725459, BHLHE23_D, MAX.chr5.77268672-77268725, EMX1_A, DSCR6, and DLX4 (see, Table 16A, Example II) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of ABLIM1, AFAP1L1, AKR1B1, ALOX5, AMN, ARL5C, BANK1, BCAT1, BEGAIN, BEST4, BHLHE23_B, BHLHE23_C, C17orf64, C1QL2, C7orf52, CALN1_B, CAV2, CD8A, CDH4_A, CDH4_B, CDH4_C, CDH4_D, CDH4_E, CDH4_F, CHST2_B, CLIP4, CR1, DLK1, DNAJC6, DNM3_A, EMX1_A, ESPN, FABP5, FAM150A, FLJ42875, GLP1R, GNG4, GYPC_A, HAND2, HES5, HNF1B_A, HNF1B_B, HOXA1_A, HOXA1_B, HOXA7_A, HOXA7_B, HOXA7_C, HOXD9, IGF2BP3_A, IGF2BP3_B, IGSF9B_A, IL15RA, INSM1, ITPKA_B, ITPRIPL1, KCNE3, KCNK17_B, LIME1, LOC100132891, LOC283999, LY6H, MAST1, MAX.chr1.158083198-158083476, MAX.chr1.228074764-228074977, MAX.chr1.46913931-46913950, MAX.chr10.130085265-130085312, MAX.chr11.68622869-68622968, MAX.chr14.101176106-101176260, MAX.chr15.96889069-96889128, MAX.chr17.8230197-8230314, MAX.chr19.46379903-46380197, MAX.chr2.97193163-97193287, MAX.chr2.97193478-97193562, MAX.chr20.1784209-1784461, MAX.chr21.44782441-44782498, MAX.chr22.23908718-23908782, MAX.chr5.145725410-145725459, MAX.chr5.178957564-178957598, MAX.chr5.180101084-180101094, MAX.chr5.42952185-42952280, MAX.chr5.42994866-42994936, MAX.chr6.27064703-27064783, MAX.chr7.152622607-152622638, MAX.chr8.145104132-145104218, MAX.chr9.136474504-136474527, MCF2L2, MSX2P1, NACAD, NID2_B, NID2_C, ODC1, OSR2_B, PAQR6, PCDH8, PIF1, PPARA, PPP2R5C, PRDM13_A, PRHOXNB, PRKCB, RBFOX3_A, RBFOX3_B, RFX8, SNCA, STAC2_A, STAC2_B, STX16_B SYT5, TIMP2, TMEFF2, TNFRSF10D, TRH_B, TRIM67, TRIM71_C, USP44_A, USP44_B, UTF1, UTS2R, VSTM2B_A, VSTM2B_B, ZFP64, and ZNF132 (see, Table 4, Example I) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of BHLHE23_C, CALN1_A, CD1D, CHST2_A, FMN2, HOXA1_A, HOXA7_A, KCNH8, LOC100132891, MAX.chr15.96889013-96889128, NACAD, TRIM67, ATP6V1B1, C17orf64, CHST2_B, DLX4, DNM3_A, EMX1_A, IGF2BP3_A, IGF2BP3_B, ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, ODC1, PLXNC1_A, PRKCB, LOC100132891, ITPRIPL1, ABLIM1, MAX.chr12.4273906-4274012, MAX.chr19.46379903-46380197, ZSCAN12, BHLHE23_D, COL23A1, KCNK9, LAYN, PLXNC1_A, RIC3, SCRT2_B, ALOX5, CDH4_E, HNF1B_B, TRH_A, MAST1, ASCL2, MAX.chr20.1784209-1784461, RBFOX_A, MAX.chr12.4273906-4274012, GAS7, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, GYPC_B, DLX6, FBN1, OSR2_A, BEST4, AJAP1_B, DSCR6, and MAX.chr11.68622869-68622968 (see, Table 11, Example I) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, GP5, DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197, ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, CHST2_B, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, ABLIM1, BHLHE23_D, ZSCAN12, GRASP, C10orf125 (see, Table 16B, Example II) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of ARL5C, BHLHE23_C, BMP6, C10orf125, C17orf64, C19orf66, CAMKV, CD1D, CDH4_E, CDH4_F, CHST2_A, CRHBP, DLX6, DNM3_A, DNM3_B, DNM3_C, ESYT3, ETS1_A, ETS1_B, FAM126A, FAM189A1, FAM20A, FAM59B, FBN1, FLRT2, FMN2, FOXP4, GAS7, GYPC_A, GYPC_B, HAND2, HES5, HMGA2, HNF1B_B, IGF2BP3_A, IGF2BP3_B, KCNH8, KCNK17_A, KCNQ2, KLHDC7B, LOC100132891, MAX.chr1.46913931-46913950, MAX.chr11.68622869-68622968, MAX.chr12.4273906-4274012, MAX.chr12.59990591-59990895, MAX.chr17.73073682-73073814, MAX.chr20.1783841-1784054, MAX.chr21.47063802-47063851, MAX.chr4.8860002-8860038, MAX.chr5.172234248-172234494, MAX.chr5.178957564-178957598, MAX.chr6.130686865-130686985, MAX.chr8.687688-687736, MAX.chr8.688863-688924, MAX.chr9.114010-114207, MPZ, NID2_A, NKX2-6, ODC1, OSR2_A, POU4F1, PRDM13_B, PRKCB, RASGRF2, RIPPLY2, SLC30A10, ST8SIA4, SYN2, TRIM71_A, TRIM71_B, TRIM71_C, UBTF, ULBP1, USP44_B, and VSTM2B_A (see, Table 5, Example I) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of BHLHE23_C, CD1D, CHST2_A, FAM126A, FMN2, HOXA1_A, HOXA7_A, KCNH8, LOC100132891, MAX.chr15.96889013-96889128, SLC30A10, TRIM67, ATP6V1B1, BANK, C10orf125, C17orf64, CHST2_B, DNM3_A, EMX1_A, GP5, IGF2BP3_A, IGF2BP3_B, ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, ODC1, PLXNC1_A, PRKCB, ST8SIA4, STX16_B UBTF, LOC100132891, ITPRIPL1, MAX.chr12.4273906-4274012, MAX.chr12.59990671-59990859, BHLHE23_D, COL23A1, KCNK9, OTX1, PLXNC1_A, HNF1B_B, MAST1, ASCL2, MAX.chr20.1784209-1784461, RBFOX_A, MAX.chr12.4273906-4274012, GAS7, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, GYPC_B, DLX6, FBN1, OSR2_A, BEST4, DSCR6, MAX.chr11.68622869-68622968 (see, Table 11, Example I) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of ATP6V1B1, LMX1B_A, BANK1, OTX1, ST8SIA4, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, ALOX5, MAX.chr19.46379903-46380197, ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, CHST2_B, ITPRIPL1, IGF2BP3_B, CDH4_E, ABLIM1, SLC30A10, C10orf125 (see, Table 16C, Example II) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of ACCN1, AJAP1_A, AJAP1_B, BEST4, CALN1_B, CBLN1_B, CDH4_E, DLX4, FOXP4, IGSF9B_B, ITPRIPL1, KCNA1, KLF16, LMX1B_A, MAST1, MAX.chr11.14926602-14927148, MAX.chr17.73073682-73073814, MAX.chr18.76734362-76734370, MAX.chr18.76734423-76734476, MAX.chr19.30719261-30719354, MAX.chr22.42679578-42679917, MAX.chr4.8860002-8860038, MAX.chr5.145725410-145725459, MAX.chr5.178957564-178957598, MAX.chr5.77268672-77268725, MAX.chr8.124173128-124173268, MPZ, PPARA, PRMT1, RBFOX3_B, RYR2_A, SALL3, SCRT2_A, SPHK2, STX16_B SYNJ2, TMEM176A, TSHZ3, and VIPR2 (see, Table 6, Example I) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of CALN1_A, LOC100132891, MAX.chr15.96889013-96889128, ATP6V1B1, C17orf64, DLX4, ITPRIPL1, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, PRKCB, ITPRIPL1, KLF16, MAX.chr12.4273906-4274012, MAX.chr19.46379903-46380197, BHLHE23_D, HNF1B_B, TRH_A, ASCL2, MAX.chr20.1784209-1784461, MAX.chr12.4273906-4274012, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, BEST4, AJAP1_B, and DSCR6 (see, Table 11, Example I) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197, CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1, IGF2BP3_B, CDH4_E, DLX4, ABLIM1, BHLHE23_D (see, Table 16D, Example II) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting C10orf93, C20orf195_A, C20orf195_B, CALN1_B, CBLN1_A, CBLN1_B, CCDC61, CCND2_A, CCND2_B, CCND2_C, EMX1_B, FAM150B, GRASP, HBM, ITPRIPL1, KCNK17_A, KIAA1949, LOC100131176, MAST1, MAX.chr1.8277285-8277316, MAX.chr1.8277479-8277527, MAX.chr11.14926602-14926729, MAX.chr11.14926860-14927148, MAX.chr15.96889013-96889128, MAX.chr18.5629721-5629791, MAX.chr19.30719261-30719354, MAX.chr22.42679767-42679917, MAX.chr5.178957564-178957598, MAX.chr5.77268672-77268725, MAX.chr6.157556793-157556856, MAX.chr8.124173030-124173395, MN1, MPZ, NR2F6, PDXK_A, PDXK_B, PTPRM, RYR2_B, SERPINB9_A, SERPINB9_B, SLC8A3, STX16_B TEPP, TOX, VIPR2, VSTM2B_A, ZNF486, ZNF626, and ZNF671 (see, Table 7, Example I) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of BHLHE23_C, CALN1_A, CD1D, HOXA7_A, LOC100132891, MAX.chr1.8277479-8277527, MAX.chr15.96889013-96889128, NACAD, ATP6V1B1, BANK1, C17orf64, DLX4, EMX1_A, FOXP4, GP5, ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, PRKCB, STX16_B UBTF, LOC100132891, ITPRIPL1, ABLIM1, MAX.chr19.46379903-46380197, ZSCAN12, BHLHE23_D, CXCL12, KCNK9, OTX1, RIC3, SCRT2_B, MAX.chr17.73073682-73073814, CDH4_E, HNF1B_B, TRH_A, MAX.chr20.1784209-1784461, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, BEST4, and DSCR6 (see, Table 11, Example I) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of ANTXR2, B3GNT5, BHLHE23_C, BMP4, CHRNA7, EPHA4, FAM171A1, FAM20A, FMNL2, FSCN1, GSTP1, HBM, IGFBP5, IL17REL, ITGA9, ITPRIPL1, KIRREL2, LRRC34, MAX.chr1.239549742-239549886, MAX.chr1.8277479-8277527, MAX.chr11.14926602-14926729, MAX.chr11.14926860-14927148, MAX.chr15.96889013-96889128, MAX.chr2.238864674-238864735, MAX.chr5.81148300-81148332, MAX.chr7.151145632-151145743, MAX.chr8.124173030-124173395, MAX.chr8.143533298-143533558, MERTK, MPZ, NID2_C, NTRK3, OLIG3_A, OLIG3_B, OSR2_C, PROM1, RGS17, SBNO2, STX16_B TBKBP1, TLX1NB, VIPR2, VN1R2, VSNL1, and ZFP64 (see, Table 8, Example I) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of MAX.chr15.96889013-96889128, ATP6V1B1, C17orf64, ITPRIPL1, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, LOC100132891, ITPRIPL1, ABLIM1, MAX.chr19.46379903-46380197, COL23A1, LAYN, OTX1, TRH_A, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968 (see, Table 11, Example I) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of CDH4_E, FLJ42875, GAD2, GRASP, ITPRIPL1, KCNA1, MAX.chr12.4273906-4274012, MAX.chr18.76734362-76734370, MAX.chr18.76734423-76734476, MAX.chr19.30719261-30719354, MAX.chr4.8859602-8859669, MAX.chr4.8860002-8860038, MAX.chr5.145725410-145725459, MAX.chr5.178957564-178957598, MAX.chr5.77268672-77268725, MPZ, NKX2-6, PRKCB, RBFOX3_B, SALL3, and VSTM2B_A (see, Table 9, Example I) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of SCRT2_B, MPZ, MAX.chr8.124173030-124173395, ITPRIPL1, ITPRIPL1, DLX4, CALN1_A, and IGF2BP3_B (see, Table 15, Example I) comprises the DNA methylation marker.

In some embodiments, a chromosomal region having an annotation selected from the group consisting of DSCR6, SCRT2_B, MPZ, MAX.chr8.124173030-124173395, OSR2_A, MAX.chr11.68622869-68622968, ITPRIPL1, MAX.chr5.145725410-145725459, BHLHE23_C, and ITPRIPL1 (see, Table 17, Example II) comprises the DNA methylation marker.

In some embodiments, such methods comprise determining the methylation state of two DNA methylation markers. In some embodiments, such methods comprise determining the methylation state of a pair of DNA methylation markers provided in a row of Table 2.

In certain embodiments, the technology provides methods for characterizing a sample (e.g., breast tissue sample; plasma sample; whole blood sample; serum sample; stool sample) obtained from a human patient. In some embodiments, such methods comprise determining a methylation state of a DNA methylation marker in the sample comprising a base in a DMR selected from a group consisting of DMR 1-327 from Table 2; comparing the methylation state of the DNA methylation marker from the patient sample to a methylation state of the DNA methylation marker from a normal control sample from a human subject who does not have a breast cancer and/or a specific form of breast cancer (e.g., triple negative breast cancer, HER2⁺ breast cancer, Luminal A breast cancer, Luminal B breast cancer, BRCA1 breast cancer, BRCA2 breast cancer); and determining a confidence interval and/or ap value of the difference in the methylation state of the human patient and the normal control sample. In some embodiments, the confidence interval is 90%, 95%, 97.5%, 98%, 99%, 99.5%, 99.9% or 99.99% and the p value is 0.1, 0.05, 0.025, 0.02, 0.01, 0.005, 0.001, or 0.0001.

In certain embodiments, the technology provides methods for characterizing a sample obtained from a human subject (e.g., breast tissue sample; plasma sample; whole blood sample; serum sample; stool sample), the method comprising reacting a nucleic acid comprising a DMR with a reagent capable of modifying DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent) to produce nucleic acid modified in a methylation-specific manner; sequencing the nucleic acid modified in a methylation-specific manner to provide a nucleotide sequence of the nucleic acid modified in a methylation-specific manner; comparing the nucleotide sequence of the nucleic acid modified in a methylation-specific manner with a nucleotide sequence of a nucleic acid comprising the DMR from a subject who does not have breast cancer to identify differences in the two sequences.

In certain embodiments, the technology provides systems for characterizing a sample obtained from a human subject (e.g., breast tissue sample; plasma sample; stool sample), the system comprising an analysis component configured to determine the methylation state of a sample, a software component configured to compare the methylation state of the sample with a control sample or a reference sample methylation state recorded in a database, and an alert component configured to determine a single value based on a combination of methylation states and alert a user of a breast cancer-associated methylation state. In some embodiments, the sample comprises a nucleic acid comprising a DMR.

In some embodiments, such systems further comprise a component for isolating a nucleic acid. In some embodiments, such systems further comprise a component for collecting a sample.

In some embodiments, the sample is a stool sample, a tissue sample, a breast tissue sample, a blood sample (e.g., plasma sample, whole blood sample, serum sample), or a urine sample.

In some embodiments, the database comprises nucleic acid sequences comprising a DMR. In some embodiments, the database comprises nucleic acid sequences from subjects who do not have a breast cancer.

Additional embodiments will be apparent to persons skilled in the relevant art based on the teachings contained herein.

Definitions

To facilitate an understanding of the present technology, a number of terms and phrases are defined below. Additional definitions are set forth throughout the detailed description.

Throughout the specification and claims, the following terms take the meanings explicitly associated herein, unless the context clearly dictates otherwise. The phrase “in one embodiment” as used herein does not necessarily refer to the same embodiment, though it may. Furthermore, the phrase “in another embodiment” as used herein does not necessarily refer to a different embodiment, although it may. Thus, as described below, various embodiments of the invention may be readily combined, without departing from the scope or spirit of the invention.

In addition, as used herein, the term “or” is an inclusive “or” operator and is equivalent to the term “and/or” unless the context clearly dictates otherwise. The term “based on” is not exclusive and allows for being based on additional factors not described, unless the context clearly dictates otherwise. In addition, throughout the specification, the meaning of “a”, “an”, and “the” include plural references. The meaning of “in” includes “in” and “on.”

The transitional phrase “consisting essentially of” as used in claims in the present application limits the scope of a claim to the specified materials or steps “and those that do not materially affect the basic and novel characteristic(s)” of the claimed invention, as discussed in In re Herz, 537 F.2d 549, 551-52, 190 USPQ 461, 463 (CCPA 1976). For example, a composition “consisting essentially of” recited elements may contain an unrecited contaminant at a level such that, though present, the contaminant does not alter the function of the recited composition as compared to a pure composition, i.e., a composition “consisting of” the recited components.

As used herein, a “nucleic acid” or “nucleic acid molecule” generally refers to any ribonucleic acid or deoxyribonucleic acid, which may be unmodified or modified DNA or RNA. “Nucleic acids” include, without limitation, single- and double-stranded nucleic acids. As used herein, the term “nucleic acid” also includes DNA as described above that contains one or more modified bases. Thus, DNA with a backbone modified for stability or for other reasons is a “nucleic acid”. The term “nucleic acid” as it is used herein embraces such chemically, enzymatically, or metabolically modified forms of nucleic acids, as well as the chemical forms of DNA characteristic of viruses and cells, including for example, simple and complex cells.

The terms “oligonucleotide” or “polynucleotide” or “nucleotide” or “nucleic acid” refer to a molecule having two or more deoxyribonucleotides or ribonucleotides, preferably more than three, and usually more than ten. The exact size will depend on many factors, which in turn depends on the ultimate function or use of the oligonucleotide. The oligonucleotide may be generated in any manner, including chemical synthesis, DNA replication, reverse transcription, or a combination thereof. Typical deoxyribonucleotides for DNA are thymine, adenine, cytosine, and guanine. Typical ribonucleotides for RNA are uracil, adenine, cytosine, and guanine.

As used herein, the terms “locus” or “region” of a nucleic acid refer to a subregion of a nucleic acid, e.g., a gene on a chromosome, a single nucleotide, a CpG island, etc.

The terms “complementary” and “complementarity” refer to nucleotides (e.g., 1 nucleotide) or polynucleotides (e.g., a sequence of nucleotides) related by the base-pairing rules. For example, the sequence 5′-A-G-T-3′ is complementary to the sequence 3′-T-C-A-5′. Complementarity may be “partial,” in which only some of the nucleic acids' bases are matched according to the base pairing rules. Or, there may be “complete” or “total” complementarity between the nucleic acids. The degree of complementarity between nucleic acid strands effects the efficiency and strength of hybridization between nucleic acid strands. This is of particular importance in amplification reactions and in detection methods that depend upon binding between nucleic acids.

The term “gene” refers to a nucleic acid (e.g., DNA or RNA) sequence that comprises coding sequences necessary for the production of an RNA, or of a polypeptide or its precursor. A functional polypeptide can be encoded by a full length coding sequence or by any portion of the coding sequence as long as the desired activity or functional properties (e.g., enzymatic activity, ligand binding, signal transduction, etc.) of the polypeptide are retained. The term “portion” when used in reference to a gene refers to fragments of that gene. The fragments may range in size from a few nucleotides to the entire gene sequence minus one nucleotide. Thus, “a nucleotide comprising at least a portion of a gene” may comprise fragments of the gene or the entire gene.

The term “gene” also encompasses the coding regions of a structural gene and includes sequences located adjacent to the coding region on both the 5′ and 3′ ends, e.g., for a distance of about 1 kb on either end, such that the gene corresponds to the length of the full-length mRNA (e.g., comprising coding, regulatory, structural and other sequences). The sequences that are located 5′ of the coding region and that are present on the mRNA are referred to as 5′ non-translated or untranslated sequences. The sequences that are located 3′ or downstream of the coding region and that are present on the mRNA are referred to as 3′ non-translated or 3′ untranslated sequences. The term “gene” encompasses both cDNA and genomic forms of a gene. In some organisms (e.g., eukaryotes), a genomic form or clone of a gene contains the coding region interrupted with non-coding sequences termed “introns” or “intervening regions” or “intervening sequences.” Introns are segments of a gene that are transcribed into nuclear RNA (hnRNA); introns may contain regulatory elements such as enhancers. Introns are removed or “spliced out” from the nuclear or primary transcript; introns therefore are absent in the messenger RNA (mRNA) transcript. The mRNA functions during translation to specify the sequence or order of amino acids in a nascent polypeptide.

In addition to containing introns, genomic forms of a gene may also include sequences located on both the 5′ and 3′ ends of the sequences that are present on the RNA transcript. These sequences are referred to as “flanking” sequences or regions (these flanking sequences are located 5′ or 3′ to the non-translated sequences present on the mRNA transcript). The 5′ flanking region may contain regulatory sequences such as promoters and enhancers that control or influence the transcription of the gene. The 3′ flanking region may contain sequences that direct the termination of transcription, posttranscriptional cleavage, and poly adenylation.

The term “wild-type” when made in reference to a gene refers to a gene that has the characteristics of a gene isolated from a naturally occurring source. The term “wild-type” when made in reference to a gene product refers to a gene product that has the characteristics of a gene product isolated from a naturally occurring source. The term “naturally-occurring” as applied to an object refers to the fact that an object can be found in nature. For example, a polypeptide or polynucleotide sequence that is present in an organism (including viruses) that can be isolated from a source in nature and which has not been intentionally modified by the hand of a person in the laboratory is naturally-occurring. A wild-type gene is often that gene or allele that is most frequently observed in a population and is thus arbitrarily designated the “normal” or “wild-type” form of the gene. In contrast, the term “modified” or “mutant” when made in reference to a gene or to a gene product refers, respectively, to a gene or to a gene product that displays modifications in sequence and/or functional properties (e.g., altered characteristics) when compared to the wild-type gene or gene product. It is noted that naturally-occurring mutants can be isolated; these are identified by the fact that they have altered characteristics when compared to the wild-type gene or gene product.

The term “allele” refers to a variation of a gene; the variations include but are not limited to variants and mutants, polymorphic loci, and single nucleotide polymorphic loci, frameshift, and splice mutations. An allele may occur naturally in a population or it might arise during the lifetime of any particular individual of the population.

Thus, the terms “variant” and “mutant” when used in reference to a nucleotide sequence refer to a nucleic acid sequence that differs by one or more nucleotides from another, usually related, nucleotide acid sequence. A “variation” is a difference between two different nucleotide sequences; typically, one sequence is a reference sequence.

“Amplification” is a special case of nucleic acid replication involving template specificity. It is to be contrasted with non-specific template replication (e.g., replication that is template-dependent but not dependent on a specific template). Template specificity is here distinguished from fidelity of replication (e.g., synthesis of the proper polynucleotide sequence) and nucleotide (ribo- or deoxyribo-) specificity. Template specificity is frequently described in terms of “target” specificity. Target sequences are “targets” in the sense that they are sought to be sorted out from other nucleic acid. Amplification techniques have been designed primarily for this sorting out.

The term “amplifying” or “amplification” in the context of nucleic acids refers to the production of multiple copies of a polynucleotide, or a portion of the polynucleotide, typically starting from a small amount of the polynucleotide (e.g., a single polynucleotide molecule), where the amplification products or amplicons are generally detectable. Amplification of polynucleotides encompasses a variety of chemical and enzymatic processes. The generation of multiple DNA copies from one or a few copies of a target or template DNA molecule during a polymerase chain reaction (PCR) or a ligase chain reaction (LCR; see, e.g., U.S. Pat. No. 5,494,810; herein incorporated by reference in its entirety) are forms of amplification. Additional types of amplification include, but are not limited to, allele-specific PCR (see, e.g., U.S. Pat. No. 5,639,611; herein incorporated by reference in its entirety), assembly PCR (see, e.g., U.S. Pat. No. 5,965,408; herein incorporated by reference in its entirety), helicase-dependent amplification (see, e.g., U.S. Pat. No. 7,662,594; herein incorporated by reference in its entirety), hot-start PCR (see, e.g., U.S. Pat. Nos. 5,773,258 and 5,338,671; each herein incorporated by reference in their entireties), intersequence-specific PCR, inverse PCR (see, e.g., Triglia, et al. (1988) Nucleic Acids Res., 16:8186; herein incorporated by reference in its entirety), ligation-mediated PCR (see, e.g., Guilfoyle, R. et al., Nucleic Acids Research, 25:1854-1858 (1997); U.S. Pat. No. 5,508,169; each of which are herein incorporated by reference in their entireties), methylation-specific PCR (see, e.g., Herman, et al., (1996) PNAS 93(13) 9821-9826; herein incorporated by reference in its entirety), miniprimer PCR, multiplex ligation-dependent probe amplification (see, e.g., Schouten, et al., (2002) Nucleic Acids Research 30(12): e57; herein incorporated by reference in its entirety), multiplex PCR (see, e.g., Chamberlain, et al., (1988) Nucleic Acids Research 16(23) 11141-11156; Ballabio, et al., (1990) Human Genetics 84(6) 571-573; Hayden, et al., (2008) BMC Genetics 9:80; each of which are herein incorporated by reference in their entireties), nested PCR, overlap-extension PCR (see, e.g., Higuchi, et al., (1988) Nucleic Acids Research 16(15) 7351-7367; herein incorporated by reference in its entirety), real time PCR (see, e.g., Higuchi, et al., (1992) Biotechnology 10:413-417; Higuchi, et al., (1993) Biotechnology 11:1026-1030; each of which are herein incorporated by reference in their entireties), reverse transcription PCR (see, e.g., Bustin, S. A. (2000) J. Molecular Endocrinology 25:169-193; herein incorporated by reference in its entirety), solid phase PCR, thermal asymmetric interlaced PCR, and Touchdown PCR (see, e.g., Don, et al., Nucleic Acids Research (1991) 19(14) 4008; Roux, K. (1994) Biotechniques 16(5) 812-814; Hecker, et al., (1996) Biotechniques 20(3) 478-485; each of which are herein incorporated by reference in their entireties). Polynucleotide amplification also can be accomplished using digital PCR (see, e.g., Kalinina, et al., Nucleic Acids Research. 25; 1999-2004, (1997); Vogelstein and Kinzler, Proc Natl Acad Sci USA. 96; 9236-41, (1999); International Patent Publication No. WO05023091A2; US Patent Application Publication No. 20070202525; each of which are incorporated herein by reference in their entireties).

The term “polymerase chain reaction” (“PCR”) refers to the method of K. B. Mullis U.S. Pat. Nos. 4,683,195, 4,683,202, and 4,965,188, that describe a method for increasing the concentration of a segment of a target sequence in a mixture of genomic or other DNA or RNA, without cloning or purification. This process for amplifying the target sequence consists of introducing a large excess of two oligonucleotide primers to the DNA mixture containing the desired target sequence, followed by a precise sequence of thermal cycling in the presence of a DNA polymerase. The two primers are complementary to their respective strands of the double stranded target sequence. To effect amplification, the mixture is denatured and the primers then annealed to their complementary sequences within the target molecule. Following annealing, the primers are extended with a polymerase so as to form a new pair of complementary strands. The steps of denaturation, primer annealing, and polymerase extension can be repeated many times (i.e., denaturation, annealing and extension constitute one “cycle”; there can be numerous “cycles”) to obtain a high concentration of an amplified segment of the desired target sequence. The length of the amplified segment of the desired target sequence is determined by the relative positions of the primers with respect to each other, and therefore, this length is a controllable parameter. By virtue of the repeating aspect of the process, the method is referred to as the “polymerase chain reaction” (“PCR”). Because the desired amplified segments of the target sequence become the predominant sequences (in terms of concentration) in the mixture, they are said to be “PCR amplified” and are “PCR products” or “amplicons.” Those of skill in the art will understand the term “PCR” encompasses many variants of the originally described method using, e.g., real time PCR, nested PCR, reverse transcription PCR (RT-PCR), single primer and arbitrarily primed PCR, etc.

Template specificity is achieved in most amplification techniques by the choice of enzyme. Amplification enzymes are enzymes that, under conditions they are used, will process only specific sequences of nucleic acid in a heterogeneous mixture of nucleic acid. For example, in the case of Q-beta replicase, MDV-1 RNA is the specific template for the replicase (Kacian et al., Proc. Natl. Acad. Sci. USA, 69:3038 [1972]). Other nucleic acid will not be replicated by this amplification enzyme. Similarly, in the case of T7 RNA polymerase, this amplification enzyme has a stringent specificity for its own promoters (Chamberlin et al, Nature, 228:227 [1970]). In the case of T4 DNA ligase, the enzyme will not ligate the two oligonucleotides or polynucleotides, where there is a mismatch between the oligonucleotide or polynucleotide substrate and the template at the ligation junction (Wu and Wallace (1989) Genomics 4:560). Finally, thermostable template-dependent DNA polymerases (e.g., Taq and Pfu DNA polymerases), by virtue of their ability to function at high temperature, are found to display high specificity for the sequences bounded and thus defined by the primers; the high temperature results in thermodynamic conditions that favor primer hybridization with the target sequences and not hybridization with non-target sequences (H. A. Erlich (ed.), PCR Technology, Stockton Press [1989]).

As used herein, the term “nucleic acid detection assay” refers to any method of determining the nucleotide composition of a nucleic acid of interest. Nucleic acid detection assay include but are not limited to, DNA sequencing methods, probe hybridization methods, structure specific cleavage assays (e.g., the INVADER assay, (Hologic, Inc.) and are described, e.g., in U.S. Pat. Nos. 5,846,717, 5,985,557, 5,994,069, 6,001,567, 6,090,543, and 6,872,816; Lyamichev et al., Nat. Biotech., 17:292 (1999), Hall et al., PNAS, USA, 97:8272 (2000), and U.S. Pat. No. 9,096,893, each of which is herein incorporated by reference in its entirety for all purposes); enzyme mismatch cleavage methods (e.g., Variagenics, U.S. Pat. Nos. 6,110,684, 5,958,692, 5,851,770, herein incorporated by reference in their entireties); polymerase chain reaction (PCR), described above; branched hybridization methods (e.g., Chiron, U.S. Pat. Nos. 5,849,481, 5,710,264, 5,124,246, and 5,624,802, herein incorporated by reference in their entireties); rolling circle replication (e.g., U.S. Pat. Nos. 6,210,884, 6,183,960 and 6,235,502, herein incorporated by reference in their entireties); NASBA (e.g., U.S. Pat. No. 5,409,818, herein incorporated by reference in its entirety); molecular beacon technology (e.g., U.S. Pat. No. 6,150,097, herein incorporated by reference in its entirety); E-sensor technology (Motorola, U.S. Pat. Nos. 6,248,229, 6,221,583, 6,013,170, and 6,063,573, herein incorporated by reference in their entireties); cycling probe technology (e.g., U.S. Pat. Nos. 5,403,711, 5,011,769, and 5,660,988, herein incorporated by reference in their entireties); Dade Behring signal amplification methods (e.g., U.S. Pat. Nos. 6,121,001, 6,110,677, 5,914,230, 5,882,867, and 5,792,614, herein incorporated by reference in their entireties); ligase chain reaction (e.g., Baranay Proc. Natl. Acad. Sci USA 88, 189-93 (1991)); and sandwich hybridization methods (e.g., U.S. Pat. No. 5,288,609, herein incorporated by reference in its entirety).

The term “amplifiable nucleic acid” refers to a nucleic acid that may be amplified by any amplification method. It is contemplated that “amplifiable nucleic acid” will usually comprise “sample template.”

The term “sample template” refers to nucleic acid originating from a sample that is analyzed for the presence of “target” (defined below). In contrast, “background template” is used in reference to nucleic acid other than sample template that may or may not be present in a sample. Background template is most often inadvertent. It may be the result of carryover or it may be due to the presence of nucleic acid contaminants sought to be purified away from the sample. For example, nucleic acids from organisms other than those to be detected may be present as background in a test sample.

The term “primer” refers to an oligonucleotide, whether occurring naturally as, e.g., a nucleic acid fragment from a restriction digest, or produced synthetically, that is capable of acting as a point of initiation of synthesis when placed under conditions in which synthesis of a primer extension product that is complementary to a nucleic acid template strand is induced, (e.g., in the presence of nucleotides and an inducing agent such as a DNA polymerase, and at a suitable temperature and pH). The primer is preferably single stranded for maximum efficiency in amplification, but may alternatively be double stranded. If double stranded, the primer is first treated to separate its strands before being used to prepare extension products. Preferably, the primer is an oligodeoxyribonucleotide. The primer must be sufficiently long to prime the synthesis of extension products in the presence of the inducing agent. The exact lengths of the primers will depend on many factors, including temperature, source of primer, and the use of the method.

The term “probe” refers to an oligonucleotide (e.g., a sequence of nucleotides), whether occurring naturally as in a purified restriction digest or produced synthetically, recombinantly, or by PCR amplification, that is capable of hybridizing to another oligonucleotide of interest. A probe may be single-stranded or double-stranded. Probes are useful in the detection, identification, and isolation of particular gene sequences (e.g., a “capture probe”). It is contemplated that any probe used in the present invention may, in some embodiments, be labeled with any “reporter molecule,” so that is detectable in any detection system, including, but not limited to enzyme (e.g., ELISA, as well as enzyme-based histochemical assays), fluorescent, radioactive, and luminescent systems. It is not intended that the present invention be limited to any particular detection system or label.

The term “target,” as used herein refers to a nucleic acid sought to be sorted out from other nucleic acids, e.g., by probe binding, amplification, isolation, capture, etc. For example, when used in reference to the polymerase chain reaction, “target” refers to the region of nucleic acid bounded by the primers used for polymerase chain reaction, while when used in an assay in which target DNA is not amplified, e.g., in some embodiments of an invasive cleavage assay, a target comprises the site at which a probe and invasive oligonucleotides (e.g., INVADER oligonucleotide) bind to form an invasive cleavage structure, such that the presence of the target nucleic acid can be detected. A “segment” is defined as a region of nucleic acid within the target sequence.

As used herein, “methylation” refers to cytosine methylation at positions C5 or N4 of cytosine, the N6 position of adenine, or other types of nucleic acid methylation. In vitro amplified DNA is usually unmethylated because typical in vitro DNA amplification methods do not retain the methylation pattern of the amplification template. However, “unmethylated DNA” or “methylated DNA” can also refer to amplified DNA whose original template was unmethylated or methylated, respectively.

Accordingly, as used herein a “methylated nucleotide” or a “methylated nucleotide base” refers to the presence of a methyl moiety on a nucleotide base, where the methyl moiety is not present in a recognized typical nucleotide base. For example, cytosine does not contain a methyl moiety on its pyrimidine ring, but 5-methylcytosine contains a methyl moiety at position 5 of its pyrimidine ring. Therefore, cytosine is not a methylated nucleotide and 5-methylcytosine is a methylated nucleotide. In another example, thymine contains a methyl moiety at position 5 of its pyrimidine ring; however, for purposes herein, thymine is not considered a methylated nucleotide when present in DNA since thymine is a typical nucleotide base of DNA.

As used herein, a “methylated nucleic acid molecule” refers to a nucleic acid molecule that contains one or more methylated nucleotides.

As used herein, a “methylation state”, “methylation profile”, and “methylation status” of a nucleic acid molecule refers to the presence of absence of one or more methylated nucleotide bases in the nucleic acid molecule. For example, a nucleic acid molecule containing a methylated cytosine is considered methylated (e.g., the methylation state of the nucleic acid molecule is methylated). A nucleic acid molecule that does not contain any methylated nucleotides is considered unmethylated.

The methylation state of a particular nucleic acid sequence (e.g., a gene marker or DNA region as described herein) can indicate the methylation state of every base in the sequence or can indicate the methylation state of a subset of the bases (e.g., of one or more cytosines) within the sequence, or can indicate information regarding regional methylation density within the sequence with or without providing precise information of the locations within the sequence the methylation occurs.

The methylation state of a nucleotide locus in a nucleic acid molecule refers to the presence or absence of a methylated nucleotide at a particular locus in the nucleic acid molecule. For example, the methylation state of a cytosine at the 7th nucleotide in a nucleic acid molecule is methylated when the nucleotide present at the 7th nucleotide in the nucleic acid molecule is 5-methylcytosine. Similarly, the methylation state of a cytosine at the 7th nucleotide in a nucleic acid molecule is unmethylated when the nucleotide present at the 7th nucleotide in the nucleic acid molecule is cytosine (and not 5-methylcytosine).

The methylation status can optionally be represented or indicated by a “methylation value” (e.g., representing a methylation frequency, fraction, ratio, percent, etc.) A methylation value can be generated, for example, by quantifying the amount of intact nucleic acid present following restriction digestion with a methylation dependent restriction enzyme or by comparing amplification profiles after bisulfite reaction or by comparing sequences of bisulfite-treated and untreated nucleic acids. Accordingly, a value, e.g., a methylation value, represents the methylation status and can thus be used as a quantitative indicator of methylation status across multiple copies of a locus. This is of particular use when it is desirable to compare the methylation status of a sequence in a sample to a threshold or reference value.

As used herein, “methylation frequency” or “methylation percent (%)” refer to the number of instances in which a molecule or locus is methylated relative to the number of instances the molecule or locus is unmethylated.

As such, the methylation state describes the state of methylation of a nucleic acid (e.g., a genomic sequence). In addition, the methylation state refers to the characteristics of a nucleic acid segment at a particular genomic locus relevant to methylation. Such characteristics include, but are not limited to, whether any of the cytosine (C) residues within this DNA sequence are methylated, the location of methylated C residue(s), the frequency or percentage of methylated C throughout any particular region of a nucleic acid, and allelic differences in methylation due to, e.g., difference in the origin of the alleles. The terms “methylation state”, “methylation profile”, and “methylation status” also refer to the relative concentration, absolute concentration, or pattern of methylated C or unmethylated C throughout any particular region of a nucleic acid in a biological sample. For example, if the cytosine (C) residue(s) within a nucleic acid sequence are methylated it may be referred to as “hypermethylated” or having “increased methylation”, whereas if the cytosine (C) residue(s) within a DNA sequence are not methylated it may be referred to as “hypomethylated” or having “decreased methylation”. Likewise, if the cytosine (C) residue(s) within a nucleic acid sequence are methylated as compared to another nucleic acid sequence (e.g., from a different region or from a different individual, etc.) that sequence is considered hypermethylated or having increased methylation compared to the other nucleic acid sequence. Alternatively, if the cytosine (C) residue(s) within a DNA sequence are not methylated as compared to another nucleic acid sequence (e.g., from a different region or from a different individual, etc.) that sequence is considered hypomethylated or having decreased methylation compared to the other nucleic acid sequence. Additionally, the term “methylation pattern” as used herein refers to the collective sites of methylated and unmethylated nucleotides over a region of a nucleic acid. Two nucleic acids may have the same or similar methylation frequency or methylation percent but have different methylation patterns when the number of methylated and unmethylated nucleotides are the same or similar throughout the region but the locations of methylated and unmethylated nucleotides are different. Sequences are said to be “differentially methylated” or as having a “difference in methylation” or having a “different methylation state” when they differ in the extent (e.g., one has increased or decreased methylation relative to the other), frequency, or pattern of methylation. The term “differential methylation” refers to a difference in the level or pattern of nucleic acid methylation in a cancer positive sample as compared with the level or pattern of nucleic acid methylation in a cancer negative sample. It may also refer to the difference in levels or patterns between patients that have recurrence of cancer after surgery versus patients who not have recurrence. Differential methylation and specific levels or patterns of DNA methylation are prognostic and predictive biomarkers, e.g., once the correct cut-off or predictive characteristics have been defined.

Methylation state frequency can be used to describe a population of individuals or a sample from a single individual. For example, a nucleotide locus having a methylation state frequency of 50% is methylated in 50% of instances and unmethylated in 50% of instances. Such a frequency can be used, for example, to describe the degree to which a nucleotide locus or nucleic acid region is methylated in a population of individuals or a collection of nucleic acids. Thus, when methylation in a first population or pool of nucleic acid molecules is different from methylation in a second population or pool of nucleic acid molecules, the methylation state frequency of the first population or pool will be different from the methylation state frequency of the second population or pool. Such a frequency also can be used, for example, to describe the degree to which a nucleotide locus or nucleic acid region is methylated in a single individual. For example, such a frequency can be used to describe the degree to which a group of cells from a tissue sample are methylated or unmethylated at a nucleotide locus or nucleic acid region.

As used herein a “nucleotide locus” refers to the location of a nucleotide in a nucleic acid molecule. A nucleotide locus of a methylated nucleotide refers to the location of a methylated nucleotide in a nucleic acid molecule.

Typically, methylation of human DNA occurs on a dinucleotide sequence including an adjacent guanine and cytosine where the cytosine is located 5′ of the guanine (also termed CpG dinucleotide sequences). Most cytosines within the CpG dinucleotides are methylated in the human genome, however some remain unmethylated in specific CpG dinucleotide rich genomic regions, known as CpG islands (see, e.g, Antequera et al. (1990) Cell 62: 503-514).

As used herein, a “CpG island” refers to a G:C-rich region of genomic DNA containing an increased number of CpG dinucleotides relative to total genomic DNA. A CpG island can be at least 100, 200, or more base pairs in length, where the G:C content of the region is at least 50% and the ratio of observed CpG frequency over expected frequency is 0.6; in some instances, a CpG island can be at least 500 base pairs in length, where the G:C content of the region is at least 55%) and the ratio of observed CpG frequency over expected frequency is 0.65. The observed CpG frequency over expected frequency can be calculated according to the method provided in Gardiner-Garden et al (1987) J. Mol. Biol. 196: 261-281. For example, the observed CpG frequency over expected frequency can be calculated according to the formula R=(A×B)/(C×D), where R is the ratio of observed CpG frequency over expected frequency, A is the number of CpG dinucleotides in an analyzed sequence, B is the total number of nucleotides in the analyzed sequence, C is the total number of C nucleotides in the analyzed sequence, and D is the total number of G nucleotides in the analyzed sequence. Methylation state is typically determined in CpG islands, e.g., at promoter regions. It will be appreciated though that other sequences in the human genome are prone to DNA methylation such as CpA and CpT (see Ramsahoye (2000) Proc. Natl. Acad. Sci. USA 97: 5237-5242; Salmon and Kaye (1970) Biochim. Biophys. Acta. 204: 340-351; Grafstrom (1985) Nucleic Acids Res. 13: 2827-2842; Nyce (1986) Nucleic Acids Res. 14: 4353-4367; Woodcock (1987) Biochem. Biophys. Res. Commun. 145: 888-894).

As used herein, a “methylation-specific reagent” refers to a reagent that modifies a nucleotide of the nucleic acid molecule as a function of the methylation state of the nucleic acid molecule, or a methylation-specific reagent, refers to a compound or composition or other agent that can change the nucleotide sequence of a nucleic acid molecule in a manner that reflects the methylation state of the nucleic acid molecule. Methods of treating a nucleic acid molecule with such a reagent can include contacting the nucleic acid molecule with the reagent, coupled with additional steps, if desired, to accomplish the desired change of nucleotide sequence. Such methods can be applied in a manner in which unmethylated nucleotides (e.g., each unmethylated cytosine) is modified to a different nucleotide. For example, in some embodiments, such a reagent can deaminate unmethylated cytosine nucleotides to produce deoxy uracil residues. Examples of such reagents include, but are not limited to, a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent.

A change in the nucleic acid nucleotide sequence by a methylation-specific reagent can also result in a nucleic acid molecule in which each methylated nucleotide is modified to a different nucleotide.

The term “methylation assay” refers to any assay for determining the methylation state of one or more CpG dinucleotide sequences within a sequence of a nucleic acid.

The term “MS AP-PCR” (Methylation-Sensitive Arbitrarily-Primed Polymerase Chain Reaction) refers to the art-recognized technology that allows for a global scan of the genome using CG-rich primers to focus on the regions most likely to contain CpG dinucleotides, and described by Gonzalgo et al. (1997) Cancer Research 57: 594-599.

The term “MethyLight™” refers to the art-recognized fluorescence-based real-time PCR technique described by Eads et al. (1999) Cancer Res. 59: 2302-2306.

The term “HeavyMethyl™” refers to an assay wherein methylation specific blocking probes (also referred to herein as blockers) covering CpG positions between, or covered by, the amplification primers enable methylation-specific selective amplification of a nucleic acid sample.

The term “HeavyMethyl™ MethyLight™” assay refers to a HeavyMethyl™ MethyLight™ assay, which is a variation of the MethyLight™ assay, wherein the MethyLight™ assay is combined with methylation specific blocking probes covering CpG positions between the amplification primers.

The term “Ms-SNuPE” (Methylation-sensitive Single Nucleotide Primer Extension) refers to the art-recognized assay described by Gonzalgo & Jones (1997) Nucleic Acids Res. 25:2529-2531.

The term “MSP” (Methylation-specific PCR) refers to the art-recognized methylation assay described by Herman et al. (1996) Proc. Natl. Acad. Sci. USA 93: 9821-9826, and by U.S. Pat. No. 5,786,146.

The term “COBRA” (Combined Bisulfite Restriction Analysis) refers to the art-recognized methylation assay described by Xiong & Laird (1997) Nucleic Acids Res. 25: 2532-2534.

The term “MCA” (Methylated CpG Island Amplification) refers to the methylation assay described by Toyota et al. (1999) Cancer Res. 59: 2307-12, and in WO 00/26401A1.

As used herein, a “selected nucleotide” refers to one nucleotide of the four typically occurring nucleotides in a nucleic acid molecule (C, G, T, and A for DNA and C, G, U, and A for RNA), and can include methylated derivatives of the typically occurring nucleotides (e.g., when C is the selected nucleotide, both methylated and unmethylated C are included within the meaning of a selected nucleotide), whereas a methylated selected nucleotide refers specifically to a methylated typically occurring nucleotide and an unmethylated selected nucleotides refers specifically to an unmethylated typically occurring nucleotide.

The term “methylation-specific restriction enzyme” refers to a restriction enzyme that selectively digests a nucleic acid dependent on the methylation state of its recognition site. In the case of a restriction enzyme that specifically cuts if the recognition site is not methylated or is hemi-methylated (a methylation-sensitive enzyme), the cut will not take place (or will take place with a significantly reduced efficiency) if the recognition site is methylated on one or both strands. In the case of a restriction enzyme that specifically cuts only if the recognition site is methylated (a methylation-dependent enzyme), the cut will not take place (or will take place with a significantly reduced efficiency) if the recognition site is not methylated. Preferred are methylation-specific restriction enzymes, the recognition sequence of which contains a CG dinucleotide (for instance a recognition sequence such as CGCG or CCCGGG). Further preferred for some embodiments are restriction enzymes that do not cut if the cytosine in this dinucleotide is methylated at the carbon atom C5.

As used herein, a “different nucleotide” refers to a nucleotide that is chemically different from a selected nucleotide, typically such that the different nucleotide has Watson-Crick base-pairing properties that differ from the selected nucleotide, whereby the typically occurring nucleotide that is complementary to the selected nucleotide is not the same as the typically occurring nucleotide that is complementary to the different nucleotide. For example, when C is the selected nucleotide, U or T can be the different nucleotide, which is exemplified by the complementarity of C to G and the complementarity of U or T to A. As used herein, a nucleotide that is complementary to the selected nucleotide or that is complementary to the different nucleotide refers to a nucleotide that base-pairs, under high stringency conditions, with the selected nucleotide or different nucleotide with higher affinity than the complementary nucleotide's base-paring with three of the four typically occurring nucleotides. An example of complementarity is Watson-Crick base pairing in DNA (e.g., A-T and C-G) and RNA (e.g., A-U and C-G). Thus, for example, G base-pairs, under high stringency conditions, with higher affinity to C than G base-pairs to G, A, or T and, therefore, when C is the selected nucleotide, G is a nucleotide complementary to the selected nucleotide.

As used herein, the “sensitivity” of a given marker (or set of markers used together) refers to the percentage of samples that report a DNA methylation value above a threshold value that distinguishes between neoplastic and non-neoplastic samples. In some embodiments, a positive is defined as a histology-confirmed neoplasia that reports a DNA methylation value above a threshold value (e.g., the range associated with disease), and a false negative is defined as a histology-confirmed neoplasia that reports a DNA methylation value below the threshold value (e.g., the range associated with no disease). The value of sensitivity, therefore, reflects the probability that a DNA methylation measurement for a given marker obtained from a known diseased sample will be in the range of disease-associated measurements. As defined here, the clinical relevance of the calculated sensitivity value represents an estimation of the probability that a given marker would detect the presence of a clinical condition when applied to a subject with that condition.

As used herein, the “specificity” of a given marker (or set of markers used together) refers to the percentage of non-neoplastic samples that report a DNA methylation value below a threshold value that distinguishes between neoplastic and non-neoplastic samples. In some embodiments, a negative is defined as a histology-confirmed non-neoplastic sample that reports a DNA methylation value below the threshold value (e.g., the range associated with no disease) and a false positive is defined as a histology-confirmed non-neoplastic sample that reports a DNA methylation value above the threshold value (e.g., the range associated with disease). The value of specificity, therefore, reflects the probability that a DNA methylation measurement for a given marker obtained from a known non-neoplastic sample will be in the range of non-disease associated measurements. As defined here, the clinical relevance of the calculated specificity value represents an estimation of the probability that a given marker would detect the absence of a clinical condition when applied to a patient without that condition.

The term “AUC” as used herein is an abbreviation for the “area under a curve”. In particular it refers to the area under a Receiver Operating Characteristic (ROC) curve. The ROC curve is a plot of the true positive rate against the false positive rate for the different possible cut points of a diagnostic test. It shows the trade-off between sensitivity and specificity depending on the selected cut point (any increase in sensitivity will be accompanied by a decrease in specificity). The area under an ROC curve (AUC) is a measure for the accuracy of a diagnostic test (the larger the area the better; the optimum is 1; a random test would have a ROC curve lying on the diagonal with an area of 0.5; for reference: J. P. Egan. (1975) Signal Detection Theory and ROC Analysis, Academic Press, New York).

The term “neoplasm” as used herein refers to any new and abnormal growth of tissue. Thus, a neoplasm can be a premalignant neoplasm or a malignant neoplasm.

The term “neoplasm-specific marker,” as used herein, refers to any biological material or element that can be used to indicate the presence of a neoplasm. Examples of biological materials include, without limitation, nucleic acids, polypeptides, carbohydrates, fatty acids, cellular components (e.g., cell membranes and mitochondria), and whole cells. In some instances, markers are particular nucleic acid regions (e.g., genes, intragenic regions, specific loci, etc.). Regions of nucleic acid that are markers may be referred to, e.g., as “marker genes,” “marker regions,” “marker sequences,” “marker loci,” etc.

As used herein, the term “adenoma” refers to a benign tumor of glandular origin. Although these growths are benign, over time they may progress to become malignant.

The term “pre-cancerous” or “pre-neoplastic” and equivalents thereof refer to any cellular proliferative disorder that is undergoing malignant transformation.

A “site” of a neoplasm, adenoma, cancer, etc. is the tissue, organ, cell type, anatomical area, body part, etc. in a subject's body where the neoplasm, adenoma, cancer, etc. is located.

As used herein, a “diagnostic” test application includes the detection or identification of a disease state or condition of a subject, determining the likelihood that a subject will contract a given disease or condition, determining the likelihood that a subject with a disease or condition will respond to therapy, determining the prognosis of a subject with a disease or condition (or its likely progression or regression), and determining the effect of a treatment on a subject with a disease or condition. For example, a diagnostic can be used for detecting the presence or likelihood of a subject contracting a neoplasm or the likelihood that such a subject will respond favorably to a compound (e.g., a pharmaceutical, e.g., a drug) or other treatment.

The term “isolated” when used in relation to a nucleic acid, as in “an isolated oligonucleotide” refers to a nucleic acid sequence that is identified and separated from at least one contaminant nucleic acid with which it is ordinarily associated in its natural source. Isolated nucleic acid is present in a form or setting that is different from that in which it is found in nature. In contrast, non-isolated nucleic acids, such as DNA and RNA, are found in the state they exist in nature. Examples of non-isolated nucleic acids include: a given DNA sequence (e.g., a gene) found on the host cell chromosome in proximity to neighboring genes; RNA sequences, such as a specific mRNA sequence encoding a specific protein, found in the cell as a mixture with numerous other mRNAs which encode a multitude of proteins. However, isolated nucleic acid encoding a particular protein includes, by way of example, such nucleic acid in cells ordinarily expressing the protein, where the nucleic acid is in a chromosomal location different from that of natural cells, or is otherwise flanked by a different nucleic acid sequence than that found in nature. The isolated nucleic acid or oligonucleotide may be present in single-stranded or double-stranded form. When an isolated nucleic acid or oligonucleotide is to be utilized to express a protein, the oligonucleotide will contain at a minimum the sense or coding strand (i.e., the oligonucleotide may be single-stranded), but may contain both the sense and anti-sense strands (i.e., the oligonucleotide may be double-stranded). An isolated nucleic acid may, after isolation from its natural or typical environment, by be combined with other nucleic acids or molecules. For example, an isolated nucleic acid may be present in a host cell in which into which it has been placed, e.g., for heterologous expression.

The term “purified” refers to molecules, either nucleic acid or amino acid sequences that are removed from their natural environment, isolated, or separated. An “isolated nucleic acid sequence” may therefore be a purified nucleic acid sequence. “Substantially purified” molecules are at least 60% free, preferably at least 75% free, and more preferably at least 90% free from other components with which they are naturally associated. As used herein, the terms “purified” or “to purify” also refer to the removal of contaminants from a sample. The removal of contaminating proteins results in an increase in the percent of polypeptide or nucleic acid of interest in the sample. In another example, recombinant polypeptides are expressed in plant, bacterial, yeast, or mammalian host cells and the polypeptides are purified by the removal of host cell proteins; the percent of recombinant polypeptides is thereby increased in the sample.

The term “composition comprising” a given polynucleotide sequence or polypeptide refers broadly to any composition containing the given polynucleotide sequence or polypeptide. The composition may comprise an aqueous solution containing salts (e.g., NaCl), detergents (e.g., SDS), and other components (e.g., Denhardt's solution, dry milk, salmon sperm DNA, etc.).

The term “sample” is used in its broadest sense. In one sense it can refer to an animal cell or tissue. In another sense, it refers to a specimen or culture obtained from any source, as well as biological and environmental samples. Biological samples may be obtained from plants or animals (including humans) and encompass fluids, solids, tissues, and gases. Environmental samples include environmental material such as surface matter, soil, water, and industrial samples. These examples are not to be construed as limiting the sample types applicable to the present invention.

As used herein, a “remote sample” as used in some contexts relates to a sample indirectly collected from a site that is not the cell, tissue, or organ source of the sample. For instance, when sample material originating from the pancreas is assessed in a stool sample (e.g., not from a sample taken directly from a breast), the sample is a remote sample.

As used herein, the terms “patient” or “subject” refer to organisms to be subject to various tests provided by the technology. The term “subject” includes animals, preferably mammals, including humans. In a preferred embodiment, the subject is a primate. In an even more preferred embodiment, the subject is a human. Further with respect to diagnostic methods, a preferred subject is a vertebrate subject. A preferred vertebrate is warm-blooded; a preferred warm-blooded vertebrate is a mammal. A preferred mammal is most preferably a human. As used herein, the term “subject” includes both human and animal subjects. Thus, veterinary therapeutic uses are provided herein. As such, the present technology provides for the diagnosis of mammals such as humans, as well as those mammals of importance due to being endangered, such as Siberian tigers; of economic importance, such as animals raised on farms for consumption by humans; and/or animals of social importance to humans, such as animals kept as pets or in zoos. Examples of such animals include but are not limited to: carnivores such as cats and dogs; swine, including pigs, hogs, and wild boars; ruminants and/or ungulates such as cattle, oxen, sheep, giraffes, deer, goats, bison, and camels; pinnipeds; and horses. Thus, also provided is the diagnosis and treatment of livestock, including, but not limited to, domesticated swine, ruminants, ungulates, horses (including race horses), and the like. The presently-disclosed subject matter further includes a system for diagnosing a lung cancer in a subject. The system can be provided, for example, as a commercial kit that can be used to screen for a risk of lung cancer or diagnose a lung cancer in a subject from whom a biological sample has been collected. An exemplary system provided in accordance with the present technology includes assessing the methylation state of a marker described herein.

As used herein, the term “kit” refers to any delivery system for delivering materials. In the context of reaction assays, such delivery systems include systems that allow for the storage, transport, or delivery of reaction reagents (e.g., oligonucleotides, enzymes, etc. in the appropriate containers) and/or supporting materials (e.g., buffers, written instructions for performing the assay etc.) from one location to another. For example, kits include one or more enclosures (e.g., boxes) containing the relevant reaction reagents and/or supporting materials. As used herein, the term “fragmented kit” refers to delivery systems comprising two or more separate containers that each contain a subportion of the total kit components. The containers may be delivered to the intended recipient together or separately. For example, a first container may contain an enzyme for use in an assay, while a second container contains oligonucleotides. The term “fragmented kit” is intended to encompass kits containing Analyte specific reagents (ASR's) regulated under section 520(e) of the Federal Food, Drug, and Cosmetic Act, but are not limited thereto. Indeed, any delivery system comprising two or more separate containers that each contains a subportion of the total kit components are included in the term “fragmented kit.” In contrast, a “combined kit” refers to a delivery system containing all of the components of a reaction assay in a single container (e.g., in a single box housing each of the desired components). The term “kit” includes both fragmented and combined kits.

As used herein, the term “breast cancer” refers generally to the uncontrolled growth of breast tissue and, more specifically, to a condition characterized by anomalous rapid proliferation of abnormal cells in one or both breasts of a subject. The abnormal cells often are referred to as malignant or “neoplastic cells,” which are transformed cells that can form a solid tumor. The term “tumor” refers to an abnormal mass or population of cells (i.e., two or more cells) that result from excessive or abnormal cell division, whether malignant or benign, and pre-cancerous and cancerous cells. Malignant tumors are distinguished from benign growths or tumors in that, in addition to uncontrolled cellular proliferation, they can invade surrounding tissues and can metastasize.

As used herein, the term “HER2⁺ breast cancer” refers to breast cancers wherein at least a portion of the cancer cells express elevated levels of HER2 protein (HER2 (from human epidermal growth factor receptor 2) or HER2/neu) which promotes rapid growth of cells.

As used herein, the term “Luminal A breast cancer” refers to breast cancers wherein at least a portion of the cancer cells are estrogen receptor (ER) positive and progesterone receptor (PR) positive, but negative for HER2.

As used herein, the term “Luminal B breast cancer” refers to breast cancers wherein at least a portion of the cancer cells are ER positive, HER2 positive, and negative for PR.

As used herein, the term “triple negative breast cancer” refers to breast cancers wherein at least a portion of the cancer cells are negative for ER, HER2, and PR.

As used herein, the term “HER2⁺ breast cancer” refers to breast cancers wherein at least a portion of the cancer cells are negative for ER and PR, but positive for HER2.

As used herein, the term “BRCA1 breast cancer” refers to breast cancers wherein at least a portion of the cancer cells are characterized with a mutation in the BRCA1 gene and/or reduced wild type BRCA1 expression.

As used herein, the term “BRCA2 breast cancer” refers to breast cancers wherein at least a portion of the cancer cells are characterized with a mutation in the BRCA2 gene and/or reduced wild type BRCA2 expression.

As used herein the term “ductal carcinoma in situ” (DCIS) refers to a non-invasive cancer where abnormal cells are found in the lining of the breast milk duct. “Low grade” DCIS refers to a DCIS that is nuclear grade 1 or has a low mitotic rate. “High grade” DCIS refers to a DCIS that nuclear grade 3 or has a high mitotic rate. “Invasive” DCIS refers to a ductal carcinoma that has spread to non-ductal tissue.

As used herein, the term “information” refers to any collection of facts or data. In reference to information stored or processed using a computer system(s), including but not limited to internets, the term refers to any data stored in any format (e.g., analog, digital, optical, etc.). As used herein, the term “information related to a subject” refers to facts or data pertaining to a subject (e.g., a human, plant, or animal). The term “genomic information” refers to information pertaining to a genome including, but not limited to, nucleic acid sequences, genes, percentage methylation, allele frequencies, RNA expression levels, protein expression, phenotypes correlating to genotypes, etc. “Allele frequency information” refers to facts or data pertaining to allele frequencies, including, but not limited to, allele identities, statistical correlations between the presence of an allele and a characteristic of a subject (e.g., a human subject), the presence or absence of an allele in an individual or population, the percentage likelihood of an allele being present in an individual having one or more particular characteristics, etc.

DETAILED DESCRIPTION

In this detailed description of the various embodiments, for purposes of explanation, numerous specific details are set forth to provide a thorough understanding of the embodiments disclosed. One skilled in the art will appreciate, however, that these various embodiments may be practiced with or without these specific details. In other instances, structures and devices are shown in block diagram form. Furthermore, one skilled in the art can readily appreciate that the specific sequences in which methods are presented and performed are illustrative and it is contemplated that the sequences can be varied and still remain within the spirit and scope of the various embodiments disclosed herein.

Provided herein is technology for breast cancer screening and particularly, but not exclusively, to methods, compositions, and related uses for detecting the presence of specific forms of breast cancer (e.g., triple negative breast cancer, HER2⁺ breast cancer, Luminal A breast cancer, Luminal B breast cancer, BRCA1 breast cancer, BRCA2 breast cancer). As the technology is described herein, the section headings used are for organizational purposes only and are not to be construed as limiting the subject matter in any way.

Indeed, as described in Examples I, II and III, experiments conducted during the course for identifying embodiments for the present invention identified a novel set of 327 differentially methylated regions (DMRs) for discriminating cancer of the breast derived DNA from non-neoplastic control DNA. From these 327 novel DNA methylation markers, further experiments identified markers capable of distinguishing different types of breast cancer from normal breast tissue. For example, separate sets of DMRs were identified capable of distinguishing 1) triple negative breast cancer tissue from normal breast tissue, 2) HER2⁺ breast cancer tissue from normal breast tissue, 3) Luminal A breast cancer tissue from normal breast tissue, 4) Luminal B breast cancer tissue from normal breast tissue, 5) BRCA1 breast cancer tissue from normal breast tissue, 6) BRCA2 breast cancer tissue from normal breast tissue, and 7) invasive breast cancer tissue from normal breast tissue. In addition, DMRs were identified capable of distinguishing between ductal carcinoma in situ high grade (DCIS-HG) breast cancer tissue from ductal carcinoma in situ low grade (DCIS-LG) breast tissue.

Although the disclosure herein refers to certain illustrated embodiments, it is to be understood that these embodiments are presented by way of example and not by way of limitation.

In particular aspects, the present technology provides compositions and methods for identifying, determining, and/or classifying a cancer such as breast cancer. The methods comprise determining the methylation status of at least one methylation marker in a biological sample isolated from a subject (e.g., stool sample, breast tissue sample, plasma sample), wherein a change in the methylation state of the marker is indicative of the presence, class, or site of a breast cancer. Particular embodiments relate to markers comprising a differentially methylated region (DMR, e.g., DMR 1-327, see Table 2) that are used for diagnosis (e.g., screening) of various types of breast cancer (e.g., triple negative breast cancer, HER2⁺ breast cancer, Luminal A breast cancer, Luminal B breast cancer, BRCA1 breast cancer, BRCA2 breast cancer).

In addition to embodiments wherein the methylation analysis of at least one marker, a region of a marker, or a base of a marker comprising a DMR (e.g., DMR, e.g., DMR 1-327) provided herein and listed in Table 2 is analyzed, the technology also provides panels of markers comprising at least one marker, region of a marker, or base of a marker comprising a DMR with utility for the detection of cancers, in particular breast cancer.

Some embodiments of the technology are based upon the analysis of the CpG methylation status of at least one marker, region of a marker, or base of a marker comprising a DMR.

In some embodiments, the present technology provides for the use of a reagent that modifies DNA in a methylation-specific manner (e.g., a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent) in combination with one or more methylation assays to determine the methylation status of CpG dinucleotide sequences within at least one marker comprising a DMR (e.g., DMR 1-327, see Table 2). Genomic CpG dinucleotides can be methylated or unmethylated (alternatively known as up- and down-methylated respectively). However the methods of the present invention are suitable for the analysis of biological samples of a heterogeneous nature, e.g., a low concentration of tumor cells, or biological materials therefrom, within a background of a remote sample (e.g., blood, organ effluent, or stool). Accordingly, when analyzing the methylation status of a CpG position within such a sample one may use a quantitative assay for determining the level (e.g., percent, fraction, ratio, proportion, or degree) of methylation at a particular CpG position.

According to the present technology, determination of the methylation status of CpG dinucleotide sequences in markers comprising a DMR has utility both in the diagnosis and characterization of cancers such as breast cancer.

Combinations of Markers

In some embodiments, the technology relates to assessing the methylation state of combinations of markers comprising a DMR from Table 2 (e.g., DMR Nos. 1-327). In some embodiments, assessing the methylation state of more than one marker increases the specificity and/or sensitivity of a screen or diagnostic for identifying a neoplasm in a subject (e.g., a specific form of breast cancer).

Various cancers are predicted by various combinations of markers, e.g., as identified by statistical techniques related to specificity and sensitivity of prediction. The technology provides methods for identifying predictive combinations and validated predictive combinations for some cancers.

Methods for Assaying Methylation State

In certain embodiments, methods for analyzing a nucleic acid for the presence of 5-methylcytosine involves treatment of DNA with a reagent that modifies DNA in a methylation-specific manner. Examples of such reagents include, but are not limited to, a methylation-sensitive restriction enzyme, a methylation-dependent restriction enzyme, and a bisulfite reagent.

A frequently used method for analyzing a nucleic acid for the presence of 5-methylcytosine is based upon the bisulfite method described by Frommer, et al. for the detection of 5-methylcytosines in DNA (Frommer et al. (1992) Proc. Natl. Acad. Sci. USA 89: 1827-31 explicitly incorporated herein by reference in its entirety for all purposes) or variations thereof. The bisulfite method of mapping 5-methylcytosines is based on the observation that cytosine, but not 5-methylcytosine, reacts with hydrogen sulfite ion (also known as bisulfite). The reaction is usually performed according to the following steps: first, cytosine reacts with hydrogen sulfite to form a sulfonated cytosine. Next, spontaneous deamination of the sulfonated reaction intermediate results in a sulfonated uracil. Finally, the sulfonated uracil is desulfonated under alkaline conditions to form uracil. Detection is possible because uracil base pairs with adenine (thus behaving like thymine), whereas 5-methylcytosine base pairs with guanine (thus behaving like cytosine). This makes the discrimination of methylated cytosines from non-methylated cytosines possible by, e.g., bisulfite genomic sequencing (Grigg G, & Clark S, Bioessays (1994) 16: 431-36; Grigg G, DNA Seq. (1996) 6: 189-98), methylation-specific PCR (MSP) as is disclosed, e.g., in U.S. Pat. No. 5,786,146, or using an assay comprising sequence-specific probe cleavage, e.g., a QuARTS flap endonuclease assay (see, e.g., Zou et al. (2010) “Sensitive quantification of methylated markers with a novel methylation specific technology” Clin Chem 56: A199; and in U.S. Pat. Nos. 8,361,720; 8,715,937; 8,916,344; and 9,212,392.

Some conventional technologies are related to methods comprising enclosing the DNA to be analyzed in an agarose matrix, thereby preventing the diffusion and renaturation of the DNA (bisulfite only reacts with single-stranded DNA), and replacing precipitation and purification steps with a fast dialysis (Olek A, et al. (1996) “A modified and improved method for bisulfite based cytosine methylation analysis” Nucleic Acids Res. 24: 5064-6). It is thus possible to analyze individual cells for methylation status, illustrating the utility and sensitivity of the method. An overview of conventional methods for detecting 5-methylcytosine is provided by Rein, T., et al. (1998) Nucleic Acids Res. 26: 2255.

The bisulfite technique typically involves amplifying short, specific fragments of a known nucleic acid subsequent to a bisulfite treatment, then either assaying the product by sequencing (Olek & Walter (1997) Nat. Genet. 17: 275-6) or a primer extension reaction (Gonzalgo & Jones (1997) Nucleic Acids Res. 25: 2529-31; WO 95/00669; U.S. Pat. No. 6,251,594) to analyze individual cytosine positions. Some methods use enzymatic digestion (Xiong & Laird (1997) Nucleic Acids Res. 25: 2532-4). Detection by hybridization has also been described in the art (Olek et al., WO 99/28498). Additionally, use of the bisulfite technique for methylation detection with respect to individual genes has been described (Grigg & Clark (1994) Bioessays 16: 431-6; Zeschnigk et al. (1997) Hum Mol Genet. 6: 387-95; Feil et al. (1994) Nucleic Acids Res. 22: 695; Martin et al. (1995) Gene 157: 261-4; WO 9746705; WO 9515373).

Various methylation assay procedures can be used in conjunction with bisulfite treatment according to the present technology. These assays allow for determination of the methylation state of one or a plurality of CpG dinucleotides (e.g., CpG islands) within a nucleic acid sequence. Such assays involve, among other techniques, sequencing of bisulfite-treated nucleic acid, PCR (for sequence-specific amplification), Southern blot analysis, and use of methylation-specific restriction enzymes, e.g., methylation-sensitive or methylation-dependent enzymes.

For example, genomic sequencing has been simplified for analysis of methylation patterns and 5-methylcytosine distributions by using bisulfite treatment (Frommer et al. (1992) Proc. Natl. Acad. Sci. USA 89: 1827-1831). Additionally, restriction enzyme digestion of PCR products amplified from bisulfite-converted DNA finds use in assessing methylation state, e.g., as described by Sadri & Hornsby (1997) Nucl. Acids Res. 24: 5058-5059 or as embodied in the method known as COBRA (Combined Bisulfite Restriction Analysis) (Xiong & Laird (1997) Nucleic Acids Res. 25: 2532-2534).

COBRA™ analysis is a quantitative methylation assay useful for determining DNA methylation levels at specific loci in small amounts of genomic DNA (Xiong & Laird, Nucleic Acids Res. 25:2532-2534, 1997). Briefly, restriction enzyme digestion is used to reveal methylation-dependent sequence differences in PCR products of sodium bisulfite-treated DNA. Methylation-dependent sequence differences are first introduced into the genomic DNA by standard bisulfite treatment according to the procedure described by Frommer et al. (Proc. Natl. Acad. Sci. USA 89:1827-1831, 1992). PCR amplification of the bisulfite converted DNA is then performed using primers specific for the CpG islands of interest, followed by restriction endonuclease digestion, gel electrophoresis, and detection using specific, labeled hybridization probes. Methylation levels in the original DNA sample are represented by the relative amounts of digested and undigested PCR product in a linearly quantitative fashion across a wide spectrum of DNA methylation levels. In addition, this technique can be reliably applied to DNA obtained from microdissected paraffin-embedded tissue samples.

Typical reagents (e.g., as might be found in a typical COBRA™-based kit) for COBRA™ analysis may include, but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, DMR, regions of genes, regions of markers, bisulfite treated DNA sequence, CpG island, etc.); restriction enzyme and appropriate buffer; gene-hybridization oligonucleotide; control hybridization oligonucleotide; kinase labeling kit for oligonucleotide probe; and labeled nucleotides. Additionally, bisulfite conversion reagents may include: DNA denaturation buffer; sulfonation buffer; DNA recovery reagents or kits (e.g., precipitation, ultrafiltration, affinity column); desulfonation buffer; and DNA recovery components. Assays such as “MethyLight™” (a fluorescence-based real-time PCR technique) (Eads et al., Cancer Res. 59:2302-2306, 1999), Ms-SNuPE™ (Methylation-sensitive Single Nucleotide Primer Extension) reactions (Gonzalgo & Jones, Nucleic Acids Res. 25:2529-2531, 1997), methylation-specific PCR (“MSP”; Herman et al., Proc. Natl. Acad. Sci. USA 93:9821-9826, 1996; U.S. Pat. No. 5,786,146), and methylated CpG island amplification (“MCA”; Toyota et al., Cancer Res. 59:2307-12, 1999) are used alone or in combination with one or more of these methods.

The “HeavyMethyl™” assay, technique is a quantitative method for assessing methylation differences based on methylation-specific amplification of bisulfite-treated DNA. Methylation-specific blocking probes (“blockers”) covering CpG positions between, or covered by, the amplification primers enable methylation-specific selective amplification of a nucleic acid sample.

The term “HeavyMethyl™ MethyLight™” assay refers to a HeavyMethyl™ MethyLight™ assay, which is a variation of the MethyLight™ assay, wherein the MethyLight™ assay is combined with methylation specific blocking probes covering CpG positions between the amplification primers. The HeavyMethyl™ assay may also be used in combination with methylation specific amplification primers.

Typical reagents (e.g., as might be found in a typical MethyLight™-based kit) for HeavyMethyl™ analysis may include, but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, regions of genes, regions of markers, bisulfite treated DNA sequence, CpG island, or bisulfite treated DNA sequence or CpG island, etc.); blocking oligonucleotides; optimized PCR buffers and deoxynucleotides; and Taq polymerase. MSP (methylation-specific PCR) allows for assessing the methylation status of virtually any group of CpG sites within a CpG island, independent of the use of methylation-sensitive restriction enzymes (Herman et al. Proc. Natl. Acad. Sci. USA 93:9821-9826, 1996; U.S. Pat. No. 5,786,146). Briefly, DNA is modified by sodium bisulfite, which converts unmethylated, but not methylated cytosines, to uracil, and the products are subsequently amplified with primers specific for methylated versus unmethylated DNA. MSP requires only small quantities of DNA, is sensitive to 0.1% methylated alleles of a given CpG island locus, and can be performed on DNA extracted from paraffin-embedded samples. Typical reagents (e.g., as might be found in a typical MSP-based kit) for MSP analysis may include, but are not limited to: methylated and unmethylated PCR primers for specific loci (e.g., specific genes, markers, regions of genes, regions of markers, bisulfite treated DNA sequence, CpG island, etc.); optimized PCR buffers and deoxynucleotides, and specific probes.

The MethyLight™ assay is a high-throughput quantitative methylation assay that utilizes fluorescence-based real-time PCR (e.g., TaqMan®) that requires no further manipulations after the PCR step (Eads et al., Cancer Res. 59:2302-2306, 1999). Briefly, the MethyLight™ process begins with a mixed sample of genomic DNA that is converted, in a sodium bisulfite reaction, to a mixed pool of methylation-dependent sequence differences according to standard procedures (the bisulfite process converts unmethylated cytosine residues to uracil). Fluorescence-based PCR is then performed in a “biased” reaction, e.g., with PCR primers that overlap known CpG dinucleotides. Sequence discrimination occurs both at the level of the amplification process and at the level of the fluorescence detection process.

The MethyLight™ assay is used as a quantitative test for methylation patterns in a nucleic acid, e.g., a genomic DNA sample, wherein sequence discrimination occurs at the level of probe hybridization. In a quantitative version, the PCR reaction provides for a methylation specific amplification in the presence of a fluorescent probe that overlaps a particular putative methylation site. An unbiased control for the amount of input DNA is provided by a reaction in which neither the primers, nor the probe, overlie any CpG dinucleotides. Alternatively, a qualitative test for genomic methylation is achieved by probing the biased PCR pool with either control oligonucleotides that do not cover known methylation sites (e.g., a fluorescence-based version of the HeavyMethyl™ and MSP techniques) or with oligonucleotides covering potential methylation sites.

The MethyLight™ process is used with any suitable probe (e.g. a “TaqMan®” probe, a Lightcycler® probe, etc.) For example, in some applications double-stranded genomic DNA is treated with sodium bisulfite and subjected to one of two sets of PCR reactions using TaqMan® probes, e.g., with MSP primers and/or HeavyMethyl blocker oligonucleotides and a TaqMan® probe. The TaqMan® probe is dual-labeled with fluorescent “reporter” and “quencher” molecules and is designed to be specific for a relatively high GC content region so that it melts at about a 10° C. higher temperature in the PCR cycle than the forward or reverse primers. This allows the TaqMan® probe to remain fully hybridized during the PCR annealing/extension step. As the Taq polymerase enzymatically synthesizes a new strand during PCR, it will eventually reach the annealed TaqMan® probe. The Taq polymerase 5′ to 3′ endonuclease activity will then displace the TaqMan® probe by digesting it to release the fluorescent reporter molecule for quantitative detection of its now unquenched signal using a real-time fluorescent detection system.

Typical reagents (e.g., as might be found in a typical MethyLight™-based kit) for MethyLight™ analysis may include, but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, regions of genes, regions of markers, bisulfite treated DNA sequence, CpG island, etc.); TaqMan® or Lightcycler® probes; optimized PCR buffers and deoxynucleotides; and Taq polymerase.

The QM™ (quantitative methylation) assay is an alternative quantitative test for methylation patterns in genomic DNA samples, wherein sequence discrimination occurs at the level of probe hybridization. In this quantitative version, the PCR reaction provides for unbiased amplification in the presence of a fluorescent probe that overlaps a particular putative methylation site. An unbiased control for the amount of input DNA is provided by a reaction in which neither the primers, nor the probe, overlie any CpG dinucleotides. Alternatively, a qualitative test for genomic methylation is achieved by probing the biased PCR pool with either control oligonucleotides that do not cover known methylation sites (a fluorescence-based version of the HeavyMethyl™ and MSP techniques) or with oligonucleotides covering potential methylation sites.

The QM™ process can be used with any suitable probe, e.g., “TaqMan®” probes, Lightcycler® probes, in the amplification process. For example, double-stranded genomic DNA is treated with sodium bisulfite and subjected to unbiased primers and the TaqMan® probe. The TaqMan® probe is dual-labeled with fluorescent “reporter” and “quencher” molecules, and is designed to be specific for a relatively high GC content region so that it melts out at about a 10° C. higher temperature in the PCR cycle than the forward or reverse primers. This allows the TaqMan® probe to remain fully hybridized during the PCR annealing/extension step. As the Taq polymerase enzymatically synthesizes a new strand during PCR, it will eventually reach the annealed TaqMan® probe. The Taq polymerase 5′ to 3′ endonuclease activity will then displace the TaqMan® probe by digesting it to release the fluorescent reporter molecule for quantitative detection of its now unquenched signal using a real-time fluorescent detection system. Typical reagents (e.g., as might be found in a typical QM™-based kit) for QM™ analysis may include, but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, regions of genes, regions of markers, bisulfite treated DNA sequence, CpG island, etc.); TaqMan® or Lightcycler® probes; optimized PCR buffers and deoxynucleotides; and Taq polymerase.

The Ms-SNuPE™ technique is a quantitative method for assessing methylation differences at specific CpG sites based on bisulfite treatment of DNA, followed by single-nucleotide primer extension (Gonzalgo & Jones, Nucleic Acids Res. 25:2529-2531, 1997). Briefly, genomic DNA is reacted with sodium bisulfite to convert unmethylated cytosine to uracil while leaving 5-methylcytosine unchanged. Amplification of the desired target sequence is then performed using PCR primers specific for bisulfite-converted DNA, and the resulting product is isolated and used as a template for methylation analysis at the CpG site of interest. Small amounts of DNA can be analyzed (e.g., microdissected pathology sections) and it avoids utilization of restriction enzymes for determining the methylation status at CpG sites.

Typical reagents (e.g., as might be found in a typical Ms-SNuPE™-based kit) for Ms-SNuPE™ analysis may include, but are not limited to: PCR primers for specific loci (e.g., specific genes, markers, regions of genes, regions of markers, bisulfite treated DNA sequence, CpG island, etc.); optimized PCR buffers and deoxynucleotides; gel extraction kit; positive control primers; Ms-SNuPE™ primers for specific loci; reaction buffer (for the Ms-SNuPE reaction); and labeled nucleotides. Additionally, bisulfite conversion reagents may include: DNA denaturation buffer; sulfonation buffer; DNA recovery reagents or kit (e.g., precipitation, ultrafiltration, affinity column); desulfonation buffer; and DNA recovery components.

Reduced Representation Bisulfite Sequencing (RRBS) begins with bisulfite treatment of nucleic acid to convert all unmethylated cytosines to uracil, followed by restriction enzyme digestion (e.g., by an enzyme that recognizes a site including a CG sequence such as MspI) and complete sequencing of fragments after coupling to an adapter ligand. The choice of restriction enzyme enriches the fragments for CpG dense regions, reducing the number of redundant sequences that may map to multiple gene positions during analysis. As such, RRBS reduces the complexity of the nucleic acid sample by selecting a subset (e.g., by size selection using preparative gel electrophoresis) of restriction fragments for sequencing. As opposed to whole-genome bisulfite sequencing, every fragment produced by the restriction enzyme digestion contains DNA methylation information for at least one CpG dinucleotide. As such, RRBS enriches the sample for promoters, CpG islands, and other genomic features with a high frequency of restriction enzyme cut sites in these regions and thus provides an assay to assess the methylation state of one or more genomic loci.

A typical protocol for RRBS comprises the steps of digesting a nucleic acid sample with a restriction enzyme such as MspI, filling in overhangs and A-tailing, ligating adaptors, bisulfite conversion, and PCR. See, e.g., et al. (2005) “Genome-scale DNA methylation mapping of clinical samples at single-nucleotide resolution” Nat Methods 7: 133-6; Meissner et al. (2005) “Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis” Nucleic Acids Res. 33: 5868-77.

In some embodiments, a quantitative allele-specific real-time target and signal amplification (QuARTS) assay is used to evaluate methylation state. Three reactions sequentially occur in each QuARTS assay, including amplification (reaction 1) and target probe cleavage (reaction 2) in the primary reaction; and FRET cleavage and fluorescent signal generation (reaction 3) in the secondary reaction. When target nucleic acid is amplified with specific primers, a specific detection probe with a flap sequence loosely binds to the amplicon. The presence of the specific invasive oligonucleotide at the target binding site causes a 5′ nuclease, e.g., a FEN-1 endonuclease, to release the flap sequence by cutting between the detection probe and the flap sequence. The flap sequence is complementary to a non-hairpin portion of a corresponding FRET cassette. Accordingly, the flap sequence functions as an invasive oligonucleotide on the FRET cassette and effects a cleavage between the FRET cassette fluorophore and a quencher, which produces a fluorescent signal. The cleavage reaction can cut multiple probes per target and thus release multiple fluorophore per flap, providing exponential signal amplification. QuARTS can detect multiple targets in a single reaction well by using FRET cassettes with different dyes. See, e.g., in Zou et al. (2010) “Sensitive quantification of methylated markers with a novel methylation specific technology” Clin Chem 56: A199), and U.S. Pat. Nos. 8,361,720; 8,715,937; 8,916,344; and 9,212,392, each of which is incorporated herein by reference for all purposes.

The term “bisulfite reagent” refers to a reagent comprising bisulfite, disulfite, hydrogen sulfite, or combinations thereof, useful as disclosed herein to distinguish between methylated and unmethylated CpG dinucleotide sequences. Methods of said treatment are known in the art (e.g., PCT/EP2004/011715 and WO 2013/116375, each of which is incorporated by reference in its entirety). In some embodiments, bisulfite treatment is conducted in the presence of denaturing solvents such as but not limited to n-alkyleneglycol or diethylene glycol dimethyl ether (DME), or in the presence of dioxane or dioxane derivatives. In some embodiments the denaturing solvents are used in concentrations between 1% and 35% (v/v). In some embodiments, the bisulfite reaction is carried out in the presence of scavengers such as but not limited to chromane derivatives, e.g., 6-hydroxy-2,5,7,8,-tetramethylchromane 2-carboxylic acid or trihydroxybenzone acid and derivates thereof, e.g., Gallic acid (see: PCT/EP2004/011715, which is incorporated by reference in its entirety). In certain preferred embodiments, the bisulfite reaction comprises treatment with ammonium hydrogen sulfite, e.g., as described in WO 2013/116375.

In some embodiments, fragments of the treated DNA are amplified using sets of primer oligonucleotides according to the present invention (e.g., see Table 10) and an amplification enzyme. The amplification of several DNA segments can be carried out simultaneously in one and the same reaction vessel. Typically, the amplification is carried out using a polymerase chain reaction (PCR). Amplicons are typically 100 to 2000 base pairs in length.

In another embodiment of the method, the methylation status of CpG positions within or near a marker comprising a DMR (e.g., DMR 1-327, Table 2) may be detected by use of methylation-specific primer oligonucleotides. This technique (MSP) has been described in U.S. Pat. No. 6,265,171 to Herman. The use of methylation status specific primers for the amplification of bisulfite treated DNA allows the differentiation between methylated and unmethylated nucleic acids. MSP primer pairs contain at least one primer that hybridizes to a bisulfite treated CpG dinucleotide. Therefore, the sequence of said primers comprises at least one CpG dinucleotide. MSP primers specific for non-methylated DNA contain a “T” at the position of the C position in the CpG.

The fragments obtained by means of the amplification can carry a directly or indirectly detectable label. In some embodiments, the labels are fluorescent labels, radionuclides, or detachable molecule fragments having a typical mass that can be detected in a mass spectrometer. Where said labels are mass labels, some embodiments provide that the labeled amplicons have a single positive or negative net charge, allowing for better delectability in the mass spectrometer. The detection may be carried out and visualized by means of, e.g., matrix assisted laser desorption/ionization mass spectrometry (MALDI) or using electron spray mass spectrometry (ESI).

Methods for isolating DNA suitable for these assay technologies are known in the art. In particular, some embodiments comprise isolation of nucleic acids as described in U.S. patent application Ser. No. 13/470,251 (“Isolation of Nucleic Acids”), incorporated herein by reference in its entirety.

In some embodiments, the markers described herein find use in QUARTS assays performed on stool samples. In some embodiments, methods for producing DNA samples and, in particular, to methods for producing DNA samples that comprise highly purified, low-abundance nucleic acids in a small volume (e.g., less than 100, less than 60 microliters) and that are substantially and/or effectively free of substances that inhibit assays used to test the DNA samples (e.g., PCR, INVADER, QuARTS assays, etc.) are provided. Such DNA samples find use in diagnostic assays that qualitatively detect the presence of, or quantitatively measure the activity, expression, or amount of, a gene, a gene variant (e.g., an allele), or a gene modification (e.g., methylation) present in a sample taken from a patient. For example, some cancers are correlated with the presence of particular mutant alleles or particular methylation states, and thus detecting and/or quantifying such mutant alleles or methylation states has predictive value in the diagnosis and treatment of cancer.

Many valuable genetic markers are present in extremely low amounts in samples and many of the events that produce such markers are rare. Consequently, even sensitive detection methods such as PCR require a large amount of DNA to provide enough of a low-abundance target to meet or supersede the detection threshold of the assay. Moreover, the presence of even low amounts of inhibitory substances compromise the accuracy and precision of these assays directed to detecting such low amounts of a target. Accordingly, provided herein are methods providing the requisite management of volume and concentration to produce such DNA samples.

In some embodiments, the sample comprises blood, serum, plasma, or saliva. In some embodiments, the subject is human. Such samples can be obtained by any number of means known in the art, such as will be apparent to the skilled person. Cell free or substantially cell free samples can be obtained by subjecting the sample to various techniques known to those of skill in the art which include, but are not limited to, centrifugation and filtration. Although it is generally preferred that no invasive techniques are used to obtain the sample, it still may be preferable to obtain samples such as tissue homogenates, tissue sections, and biopsy specimens. The technology is not limited in the methods used to prepare the samples and provide a nucleic acid for testing. For example, in some embodiments, a DNA is isolated from a stool sample or from blood or from a plasma sample using direct gene capture, e.g., as detailed in U.S. Pat. Nos. 8,808,990 and 9,169,511, and in WO 2012/155072, or by a related method.

The analysis of markers can be carried out separately or simultaneously with additional markers within one test sample. For example, several markers can be combined into one test for efficient processing of multiple samples and for potentially providing greater diagnostic and/or prognostic accuracy. In addition, one skilled in the art would recognize the value of testing multiple samples (for example, at successive time points) from the same subject. Such testing of serial samples can allow the identification of changes in marker methylation states over time. Changes in methylation state, as well as the absence of change in methylation state, can provide useful information about the disease status that includes, but is not limited to, identifying the approximate time from onset of the event, the presence and amount of salvageable tissue, the appropriateness of drug therapies, the effectiveness of various therapies, and identification of the subject's outcome, including risk of future events.

The analysis of biomarkers can be carried out in a variety of physical formats. For example, the use of microtiter plates or automation can be used to facilitate the processing of large numbers of test samples. Alternatively, single sample formats could be developed to facilitate immediate treatment and diagnosis in a timely fashion, for example, in ambulatory transport or emergency room settings.

It is contemplated that embodiments of the technology are provided in the form of a kit. The comprise embodiments of the compositions, devices, apparatuses, etc. described herein, and instructions for use of the kit. Such instructions describe appropriate methods for preparing an analyte from a sample, e.g., for collecting a sample and preparing a nucleic acid from the sample. Individual components of the kit are packaged in appropriate containers and packaging (e.g., vials, boxes, blister packs, ampules, jars, bottles, tubes, and the like) and the components are packaged together in an appropriate container (e.g., a box or boxes) for convenient storage, shipping, and/or use by the user of the kit. It is understood that liquid components (e.g., a buffer) may be provided in a lyophilized form to be reconstituted by the user. Kits may include a control or reference for assessing, validating, and/or assuring the performance of the kit. For example, a kit for assaying the amount of a nucleic acid present in a sample may include a control comprising a known concentration of the same or another nucleic acid for comparison and, in some embodiments, a detection reagent (e.g., a primer) specific for the control nucleic acid. The kits are appropriate for use in a clinical setting and, in some embodiments, for use in a user's home. The components of a kit, in some embodiments, provide the functionalities of a system for preparing a nucleic acid solution from a sample. In some embodiments, certain components of the system are provided by the user.

Methods

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of ABLIM1, AJAP1_B, ASCL2, ATP6V1B1,         BANK1, CALN1_A, CALN1_B, CLIC6, DSCR6, FOXP4, GAD2, GCGR, GP5,         GRASP, HBM, HNF1B_B, KLF16, MAGI2, MAX.chr11.14926602-14927148,         MAX.chr12.4273906-4274012, MAX.chr17.73073682-73073814,         MAX.chr18.76734362-76734370, MAX.chr2.97193478-97193562,         MAX.chr22.42679578-42679917, MAX.chr4.8859253-8859329,         MAX.chr4.8859602-8859669, MAX.chr4.8860002-8860038,         MAX.chr5.145725410-145725459, MAX.chr6.157557371-157557657, MPZ,         NKX2-6, PDX1, PLXNC1_A, PPARG, PRKCB, PTPRN2, RBFOX_A, SCRT2_A,         SLC7A4, STAC2_B, STX16_A, STX16_B, TBX1, TRH_A, VSTM2B_A,         ZBTB16, ZNF132, and ZSCAN23, and     -   2) detecting triple negative breast cancer (e.g., afforded with         a sensitivity of greater than or equal to 80% and a specificity         of greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of CALN1_A, LOC100132891, NACAD,         TRIM67, ATP6V1B1, DLX4, GP5, ITPRIPL1,         MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936,         MAX.chr8.124173030-124173395, MPZ, PRKCB, ST8SIA4, STX16_B         ITPRIPL1, KLF16, MAX.chr12.4273906-4274012, KCNK9, SCRT2_B,         CDH4_E, HNF1B_B, TRH_A, MAX.chr20.1784209-1784461,         MAX.chr12.4273906-4274012, MAX.chr5.145725410-145725459,         MAX.chr5.77268672-77268725, and DSCR6, and     -   2) detecting triple negative breast cancer (e.g., afforded with         a sensitivity of greater than or equal to 80% and a specificity         of greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of ATP6V1B1,         MAX.chr11.14926602-14927148, PRKCB, TRH_A, MPZ, GP5, TRIM67,         MAX.chr12.4273906-4274012, CALN1_A, MAX.chr12.4273906-4274012,         MAX.chr5.42994866-42994936, SCRT2_B,         MAX.chr5.145725410-145725459, BHLHE23_D,         MAX.chr5.77268672-77268725, EMX1_A, DSCR6, and DLX4, and     -   2) detecting triple negative breast cancer (e.g., afforded with         a sensitivity of greater than or equal to 80% and a specificity         of greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of ABLIM1, AFAP1L1, AKR1B1, ALOX5,         AMN, ARL5C, BANK1, BCAT1, BEGAIN, BEST4, BHLHE23_B, BHLHE23_C,         C17orf64, C1QL2, C7orf52, CALN1_B, CAV2, CD8A, CDH4_A, CDH4_B,         CDH4_C, CDH4_D, CDH4_E, CDH4_F, CHST2_B, CLIP4, CR1, DLK1,         DNAJC6, DNM3_A, EMX1_A, ESPN, FABP5, FAM150A, FLJ42875, GLP1R,         GNG4, GYPC_A, HAND2, HES5, HNF1B_A, HNF1B_B, HOXA1_A, HOXA1_B,         HOXA7_A, HOXA7_B, HOXA7_C, HOXD9, IGF2BP3_A, IGF2BP3_B,         IGSF9B_A, IL15RA, INSM1, ITPKA_B, ITPRIPL1, KCNE3, KCNK17_B,         LIME1, LOC100132891, LOC283999, LY6H, MAST1,         MAX.chr1.158083198-158083476, MAX.chr1.228074764-228074977,         MAX.chr1.46913931-46913950, MAX.chr10.130085265-130085312,         MAX.chr11.68622869-68622968, MAX.chr14.101176106-101176260,         MAX.chr15.96889069-96889128, MAX.chr17.8230197-8230314,         MAX.chr19.46379903-46380197, MAX.chr2.97193163-97193287,         MAX.chr2.97193478-97193562, MAX.chr20.1784209-1784461,         MAX.chr21.44782441-44782498, MAX.chr22.23908718-23908782,         MAX.chr5.145725410-145725459, MAX.chr5.178957564-178957598,         MAX.chr5.180101084-180101094, MAX.chr5.42952185-42952280,         MAX.chr5.42994866-42994936, MAX.chr6.27064703-27064783,         MAX.chr7.152622607-152622638, MAX.chr8.145104132-145104218,         MAX.chr9.136474504-136474527, MCF2L2, MSX2P1, NACAD, NID2_B,         NID2_C, ODC1, OSR2_B, PAQR6, PCDH8, PIF1, PPARA, PPP2R5C,         PRDM13_A, PRHOXNB, PRKCB, RBFOX3_A, RBFOX3_B, RFX8, SNCA,         STAC2_A, STAC2_B, STX16_B SYT5, TIMP2, TMEFF2, TNFRSF10D, TRH_B,         TRIM67, TRIM71_C, USP44_A, USP44_B, UTF1, UTS2R, VSTM2B_A,         VSTM2B_B, ZFP64, and ZNF132, and     -   2) detecting HER2⁺ breast cancer (e.g., afforded with a         sensitivity of greater than or equal to 80% and a specificity of         greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of BHLHE23_C, CALN1_A, CD1D, CHST2_A,         FMN2, HOXA1_A, HOXA7_A, KCNH8, LOC100132891,         MAX.chr15.96889013-96889128, NACAD, TRIM67, ATP6V1B1, C17orf64,         CHST2_B, DLX4, DNM3_A, EMX1_A, IGF2BP3_A, IGF2BP3_B, ITPRIPL1,         LMX1B_A, MAX.chr11.14926602-14927148,         MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ,         ODC1, PLXNC1_A, PRKCB, LOC100132891, ITPRIPL1, ABLIM1,         MAX.chr12.4273906-4274012, MAX.chr19.46379903-46380197, ZSCAN12,         BHLHE23_D, COL23A1, KCNK9, LAYN, PLXNC1_A, RIC3, SCRT2_B, ALOX5,         CDH4_E, HNF1B_B, TRH_A, MAST1, ASCL2, MAX.chr20.1784209-1784461,         RBFOX_A, MAX.chr12.4273906-4274012, GAS7,         MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725,         GYPC_B, DLX6, FBN1, OSR2_A, BEST4, AJAP1_B, DSCR6, and         MAX.chr11.68622869-68622968, and     -   2) detecting HER2⁺ breast cancer (e.g., afforded with a         sensitivity of greater than or equal to 80% and a specificity of         greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of ATP6V1B1, LMX1B_A, BANK1, OTX1,         MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, GP5,         DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A,         ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B,         MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B,         MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968,         MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461,         LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197,         ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A,         CHST2_B, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, ABLIM1, BHLHE23_D,         ZSCAN12, GRASP, C10orf125, and     -   2) detecting HER2⁺ breast cancer (e.g., afforded with a         sensitivity of greater than or equal to 80% and a specificity of         greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of ARL5C, BHLHE23_C, BMP6, C10orf125,         C17orf64, C19orf66, CAMKV, CD1D, CDH4_E, CDH4_F, CHST2_A, CRHBP,         DLX6, DNM3_A, DNM3_B, DNM3_C, ESYT3, ETS1_A, ETS1_B, FAM126A,         FAM189A1, FAM20A, FAM59B, FBN1, FLRT2, FMN2, FOXP4, GAS7,         GYPC_A, GYPC_B, HAND2, HES5, HMGA2, HNF1B_B, IGF2BP3_A,         IGF2BP3_B, KCNH8, KCNK17_A, KCNQ2, KLHDC7B, LOC100132891,         MAX.chr1.46913931-46913950, MAX.chr11.68622869-68622968,         MAX.chr12.4273906-4274012, MAX.chr12.59990591-59990895,         MAX.chr17.73073682-73073814, MAX.chr20.1783841-1784054,         MAX.chr21.47063802-47063851, MAX.chr4.8860002-8860038,         MAX.chr5.172234248-172234494, MAX.chr5.178957564-178957598,         MAX.chr6.130686865-130686985, MAX.chr8.687688-687736,         MAX.chr8.688863-688924, MAX.chr9.114010-114207, MPZ, NID2_A,         NKX2-6, ODC1, OSR2_A, POU4F1, PRDM13_B, PRKCB, RASGRF2, RIPPLY2,         SLC30A10, ST8SIA4, SYN2, TRIM71_A, TRIM71_B, TRIM71_C, UBTF,         ULBP1, USP44_B, and VSTM2B_A, and     -   2) detecting Luminal A breast cancer (e.g., afforded with a         sensitivity of greater than or equal to 80% and a specificity of         greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of BHLHE23_C, CD1D, CHST2_A, FAM126A,         FMN2, HOXA1_A, HOXA7_A, KCNH8, LOC100132891,         MAX.chr15.96889013-96889128, SLC30A10, TRIM67, ATP6V1B1, BANK1,         C10orf125, C17orf64, CHST2_B, DNM3_A, EMX1_A, GP5, IGF2BP3_A,         IGF2BP3_B, ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148,         MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ,         ODC1, PLXNC1_A, PRKCB, ST8SIA4, STX16_B UBTF, LOC100132891,         ITPRIPL1, MAX.chr12.4273906-4274012,         MAX.chr12.59990671-59990859, BHLHE23_D, COL23A1, KCNK9, OTX1,         PLXNC1_A, HNF1B_B, MAST1, ASCL2, MAX.chr20.1784209-1784461,         RBFOX_A, MAX.chr12.4273906-4274012, GAS7,         MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725,         GYPC_B, DLX6, FBN1, OSR2_A, BEST4, DSCR6,         MAX.chr11.68622869-68622968, and     -   2) detecting Luminal A breast cancer (e.g., afforded with a         sensitivity of greater than or equal to 80% and a specificity of         greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting ATP6V1B1, LMX1B_A, BANK1, OTX1,         ST8SIA4, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ,         DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A,         ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B,         MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B,         MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968,         MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461,         LOC100132891, BHLHE23_D, ALOX5, MAX.chr19.46379903-46380197,         ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A,         CHST2_B, ITPRIPL1, IGF2BP3_B, CDH4_E, ABLIM1, SLC30A10,         C10orf125, and     -   2) detecting Luminal A breast cancer (e.g., afforded with a         sensitivity of greater than or equal to 80% and a specificity of         greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of ACCN1, AJAP1_A, AJAP1_B, BEST4,         CALN1_B, CBLN1_B, CDH4_E, DLX4, FOXP4, IGSF9B_B, ITPRIPL1,         KCNA1, KLF16, LMX1B_A, MAST1, MAX.chr11.14926602-14927148,         MAX.chr17.73073682-73073814, MAX.chr18.76734362-76734370,         MAX.chr18.76734423-76734476, MAX.chr19.30719261-30719354,         MAX.chr22.42679578-42679917, MAX.chr4.8860002-8860038,         MAX.chr5.145725410-145725459, MAX.chr5.178957564-178957598,         MAX.chr5.77268672-77268725, MAX.chr8.124173128-124173268, MPZ,         PPARA, PRMT1, RBFOX3_B, RYR2_A, SALL3, SCRT2_A, SPHK2, STX16_B         SYNJ2, TMEM176A, TSHZ3, and VIPR2, and     -   2) detecting Luminal B breast cancer (e.g., afforded with a         sensitivity of greater than or equal to 80% and a specificity of         greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of CALN1_A, LOC100132891,         MAX.chr15.96889013-96889128, ATP6V1B1, C17orf64, DLX4, ITPRIPL1,         MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936,         MAX.chr8.124173030-124173395, MPZ, PRKCB, ITPRIPL1, KLF16,         MAX.chr12.4273906-4274012, MAX.chr19.46379903-46380197,         BHLHE23_D, HNF1B_B, TRH_A, ASCL2, MAX.chr20.1784209-1784461,         MAX.chr12.4273906-4274012, MAX.chr5.145725410-145725459,         MAX.chr5.77268672-77268725, BEST4, AJAP1_B, and DSCR6, and     -   2) detecting Luminal B breast cancer (e.g., afforded with a         sensitivity of greater than or equal to 80% and a specificity of         greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of ATP6V1B1, LMX1B_A, BANK1, OTX1,         MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A,         TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1,         MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936,         OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459,         MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395,         MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_C, ALOX5,         MAX.chr19.46379903-46380197, CHST2_B,         MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1,         IGF2BP3_B, CDH4_E, DLX4, ABLIM1, BHLHE23_D, and     -   2) detecting Luminal B breast cancer (e.g., afforded with a         sensitivity of greater than or equal to 80% and a specificity of         greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of C10orf93, C20orf195_A, C20orf195_B,         CALN1_B, CBLN1_A, CBLN1_B, CCDC61, CCND2_A, CCND2_B, CCND2_C,         EMX1_B, FAM150B, GRASP, HBM, ITPRIPL1, KCNK17_A, KIAA1949,         LOC100131176, MAST1, MAX.chr1.8277285-8277316,         MAX.chr1.8277479-8277527, MAX.chr11.14926602-14926729,         MAX.chr11.14926860-14927148, MAX.chr15.96889013-96889128,         MAX.chr18.5629721-5629791, MAX.chr19.30719261-30719354,         MAX.chr22.42679767-42679917, MAX.chr5.178957564-178957598,         MAX.chr5.77268672-77268725, MAX.chr6.157556793-157556856,         MAX.chr8.124173030-124173395, MN1, MPZ, NR2F6, PDXK_A, PDXK_B,         PTPRM, RYR2_B, SERPINB9_A, SERPINB9_B, SLC8A3, STX16_B TEPP,         TOX, VIPR2, VSTM2B_A, ZNF486, ZNF626, and ZNF671, and     -   2) detecting BRCA1 breast cancer (e.g., afforded with a         sensitivity of greater than or equal to 80% and a specificity of         greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of BHLHE23_C, CALN1_A, CD1D, HOXA7_A,         LOC100132891, MAX.chr1.8277479-8277527,         MAX.chr15.96889013-96889128, NACAD, ATP6V1B1, BANK1, C17orf64,         DLX4, EMX1_A, FOXP4, GP5, ITPRIPL1, LMX1B_A,         MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936,         MAX.chr8.124173030-124173395, MPZ, PRKCB, STX16_B UBTF,         LOC100132891, ITPRIPL1, ABLIM1, MAX.chr19.46379903-46380197,         ZSCAN12, BHLHE23_D, CXCL12, KCNK9, OTX1, RIC3, SCRT2_B,         MAX.chr17.73073682-73073814, CDH4_E, HNF1B_B, TRH_A,         MAX.chr20.1784209-1784461, MAX.chr5.145725410-145725459,         MAX.chr5.77268672-77268725, BEST4, and DSCR6, and     -   2) detecting BRCA1 breast cancer (e.g., afforded with a         sensitivity of greater than or equal to 80% and a specificity of         greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of ANTXR2, B3GNT5, BHLHE23_C, BMP4,         CHRNA7, EPHA4, FAM171A1, FAM20A, FMNL2, FSCN1, GSTP1, HBM,         IGFBP5, IL17REL, ITGA9, ITPRIPL1, KIRREL2, LRRC34,         MAX.chr1.239549742-239549886, MAX.chr1.8277479-8277527,         MAX.chr11.14926602-14926729, MAX.chr11.14926860-14927148,         MAX.chr15.96889013-96889128, MAX.chr2.238864674-238864735,         MAX.chr5.81148300-81148332, MAX.chr7.151145632-151145743,         MAX.chr8.124173030-124173395, MAX.chr8.143533298-143533558,         MERTK, MPZ, NID2_C, NTRK3, OLIG3_A, OLIG3_B, OSR2_C, PROM1,         RGS17, SBNO2, STX16_B TBKBP1, TLX1NB, VIPR2, VN1R2, VSNL1, and         ZFP64, and     -   2) detecting BRCA2 breast cancer (e.g., afforded with a         sensitivity of greater than or equal to 80% and a specificity of         greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of MAX.chr15.96889013-96889128,         ATP6V1B1, C17orf64, ITPRIPL1, MAX.chr11.14926602-14927148,         MAX.chr5.42994866-42994936, LOC100132891, ITPRIPL1, ABLIM1,         MAX.chr19.46379903-46380197, COL23A1, LAYN, OTX1, TRH_A,         MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, and     -   2) detecting BRCA2 breast cancer (e.g., afforded with a         sensitivity of greater than or equal to 80% and a specificity of         greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of CDH4_E, FLJ42875, GAD2, GRASP,         ITPRIPL1, KCNA1, MAX.chr12.4273906-4274012,         MAX.chr18.76734362-76734370, MAX.chr18.76734423-76734476,         MAX.chr19.30719261-30719354, MAX.chr4.8859602-8859669,         MAX.chr4.8860002-8860038, MAX.chr5.145725410-145725459,         MAX.chr5.178957564-178957598, MAX.chr5.77268672-77268725, MPZ,         NKX2-6, PRKCB, RBFOX3_B, SALL3, and VSTM2B_A, and     -   2) detecting invasive breast cancer (e.g., afforded with a         sensitivity of greater than or equal to 80% and a specificity of         greater than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of SCRT2_B, MPZ,         MAX.chr8.124173030-124173395, ITPRIPL1, ITPRIPL1, DLX4, CALN1_A,         and IGF2BP3_B, and     -   2) distinguishing between ductal carcinoma in situ high grade         (DCIS-HG) breast cancer tissue from ductal carcinoma in situ low         grade (DCIS-LG) breast tissue (e.g., afforded with a sensitivity         of greater than or equal to 80% and a specificity of greater         than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of SCRT2_B, ITPRIPL1, and         MAX.chr8.124173030-12417339, and     -   2) distinguishing between ductal carcinoma in situ high grade         (DCIS-HG) breast cancer tissue from ductal carcinoma in situ low         grade (DCIS-LG) breast tissue (e.g., afforded with a sensitivity         of greater than or equal to 100% and a specificity of greater         than or equal to 91%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) contacting a nucleic acid (e.g., genomic DNA, e.g., isolated         from body fluids such as blood or plasma or breast tissue)         obtained from the subject with at least one reagent or series of         reagents that distinguishes between methylated and         non-methylated CpG dinucleotides within at least one marker         selected from a chromosomal region having an annotation selected         from the group consisting of DSCR6, SCRT2_B, MPZ,         MAX.chr8.124173030-124173395, OSR2_A,         MAX.chr11.68622869-68622968, ITPRIPL1,         MAX.chr5.145725410-145725459, BHLHE23_C, and ITPRIPL1, and     -   2) distinguishing between ductal carcinoma in situ high grade         (DCIS-HG) breast cancer tissue from ductal carcinoma in situ low         grade (DCIS-LG) breast tissue (e.g., afforded with a sensitivity         of greater than or equal to 80% and a specificity of greater         than or equal to 80%).

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) measuring a methylation level for one or more genes in a         biological sample of a human individual through treating genomic         DNA in the biological sample with a reagent that modifies DNA in         a methylation-specific manner (e.g., wherein the reagent is a         bisulfite reagent, a methylation-sensitive restriction enzyme,         or a methylation-dependent restriction enzyme), wherein the one         or more genes is selected from one of the following groups:         -   (i) BHLHE23_C, CALN1_A, CD1D, HOXA7_A, LOC100132891,             MAX.chr1.8277479-8277527, MAX.chr15.96889013-96889128,             NACAD, ATP6V1B1, BANK1, C17orf64, DLX4, EMX1_A, FOXP4, GP5,             ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148,             MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395,             MPZ, PRKCB, STX16_B UBTF, LOC100132891, ITPRIPL1, ABLIM1,             MAX.chr19.46379903-46380197, ZSCAN12, BHLHE23_D, CXCL12,             KCNK9, OTX1, RIC3, SCRT2_B, MAX.chr17.73073682-73073814,             CDH4_E, HNF1B_B, TRH_A, MAX.chr20.1784209-1784461,             MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725,             BEST4, and DSCR6;         -   (ii) MAX.chr15.96889013-96889128, ATP6V1B1, C17orf64,             ITPRIPL1, MAX.chr11.14926602-14927148,             MAX.chr5.42994866-42994936, LOC100132891, ITPRIPL1, ABLIM1,             MAX.chr19.46379903-46380197, COL23A1, LAYN, OTX1, TRH_A,             MAX.chr5.145725410-145725459, and             MAX.chr11.68622869-68622968;         -   (iii) ATP6V1B1, MAX.chr11.14926602-14927148, PRKCB, TRH_A,             MPZ, GP5, TRIM67, MAX.chr12.4273906-4274012, CALN1_A,             MAX.chr12.4273906-4274012, MAX.chr5.42994866-42994936,             SCRT2_B, MAX.chr5.145725410-145725459, BHLHE23_D,             MAX.chr5.77268672-77268725, EMX1_A, DSCR6, and DLX4;         -   (iv) ATP6V1B1, LMX1B_A, BANK1, OTX1,             MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, GP5,             DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012,             CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B,             MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B,             MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968,             MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461,             LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197,             ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A,             CHST2_B, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, ABLIM1,             BHLHE23_D, ZSCAN12, GRASP, and C10orf125;         -   (v) ATP6V1B1, LMX1B_A, BANK1, OTX1, ST8SIA4,             MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ,             DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012,             CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B,             MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B,             MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968,             MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461,             LOC100132891, BHLHE23_D, ALOX5, MAX.chr19.46379903-46380197,             ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A,             CHST2_B, ITPRIPL1, IGF2BP3_B, CDH4_E, ABLIM1, SLC30A10,             ClOorfl25;         -   (vi) ATP6V1B1, LMX1B_A, BANK1, OTX1,             MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ,             DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012,             CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B,             MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B,             MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968,             MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461,             LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197,             CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A,             DSCR6, ITPRIPL1, IGF2BP3_B, CDH4_E, DLX4, ABLIM1, BHLHE23_D;             and         -   (vii) DSCR6, SCRT2_B, MPZ, MAX.chr8.124173030-124173395,             OSR2_A, MAX.chr11.68622869-68622968, ITPRIPL1,             MAX.chr5.145725410-145725459, BHLHE23_C, ITPRIPL1;     -   2) amplifying the treated genomic DNA using a set of primers for         the selected one or more genes; and     -   3) determining the methylation level of the one or more genes by         polymerase chain reaction, nucleic acid sequencing, mass         spectrometry, methylation-specific nuclease, mass-based         separation, and target capture.

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) measuring an amount of at least one methylated marker gene in         DNA from the sample, wherein the one or more genes is selected         from one of the following groups:         -   (i) BHLHE23_C, CALN1_A, CD1D, HOXA7_A, LOC100132891,             MAX.chr1.8277479-8277527, MAX.chr15.96889013-96889128,             NACAD, ATP6V1B1, BANK1, C17orf64, DLX4, EMX1_A, FOXP4, GP5,             ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148,             MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395,             MPZ, PRKCB, STX16_B UBTF, LOC100132891, ITPRIPL1, ABLIM1,             MAX.chr19.46379903-46380197, ZSCAN12, BHLHE23_D, CXCL12,             KCNK9, OTX1, RIC3, SCRT2_B, MAX.chr17.73073682-73073814,             CDH4_E, HNF1B_B, TRH_A, MAX.chr20.1784209-1784461,             MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725,             BEST4, and DSCR6;         -   (ii) MAX.chr15.96889013-96889128, ATP6V1B1, C17orf64,             ITPRIPL1, MAX.chr11.14926602-14927148,             MAX.chr5.42994866-42994936, LOC100132891, ITPRIPL1, ABLIM1,             MAX.chr19.46379903-46380197, COL23A1, LAYN, OTX1, TRH_A             MAX.chr5.145725410-145725459, and             MAX.chr11.68622869-68622968;         -   (iii) ATP6V1B1, MAX.chr11.14926602-14927148, PRKCB, TRH_A,             MPZ, GP5, TRIM67, MAX.chr12.4273906-4274012, CALN1_A,             MAX.chr12.4273906-4274012, MAX.chr5.42994866-42994936,             SCRT2_B, MAX.chr5.145725410-145725459, BHLHE23_D,             MAX.chr5.77268672-77268725, EMX1_A, DSCR6, and DLX4;         -   (iv) ATP6V1B1, LMX1B_A, BANK1, OTX1,             MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, GP5,             DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012,             CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B,             MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B,             MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968,             MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461,             LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197,             ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A,             CHST2_B, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, ABLIM1,             BHLHE23_D, ZSCAN12, GRASP, and C10orf125;         -   (v) ATP6V1B1, LMX1B_A, BANK, OTX1, ST8SIA4,             MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ,             DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012,             CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B,             MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B,             MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968,             MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461,             LOC100132891, BHLHE23_D, ALOX5, MAX.chr19.46379903-46380197,             ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A,             CHST2_B, ITPRIPL1, IGF2BP3_B, CDH4_E, ABLIM1, SLC30A10,             C10orf125;         -   (vi) ATP6V1B1, LMX1B_A, BANK, OTX1,             MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ,             DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012,             CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B,             MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B,             MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968,             MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461,             LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197,             CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A,             DSCR6, ITPRIPL1, IGF2BP3_B, CDH4_E, DLX4, ABLIM1, BHLHE23_D;             and         -   (vii) DSCR6, SCRT2_B, MPZ, MAX.chr8.124173030-124173395,             OSR2_A, MAX.chr11.68622869-68622968, ITPRIPL1,             MAX.chr5.145725410-145725459, BHLHE23_C, ITPRIPL1;     -   2) measuring the amount of at least one reference marker in the         DNA; and     -   3) calculating a value for the amount of the at least one         methylated marker gene measured in the DNA as a percentage of         the amount of the reference marker gene measured in the DNA,         wherein the value indicates the amount of the at least one         methylated marker DNA measured in the sample.

In some embodiments of the technology, methods are provided that comprise the following steps:

-   -   1) measuring a methylation level of a CpG site for one or more         genes in a biological sample of a human individual through         treating genomic DNA in the biological sample with bisulfite a         reagent capable of modifying DNA in a methylation-specific         manner (e.g., a methylation-sensitive restriction enzyme, a         methylation-dependent restriction enzyme, and a bisulfite         reagent);     -   2) amplifying the modified genomic DNA using a set of primers         for the selected one or more genes; and     -   3) determining the methylation level of the CpG site by         methylation-specific PCR, quantitative methylation-specific PCR,         methylation-sensitive DNA restriction enzyme analysis,         quantitative bisulfite pyrosequencing, or bisulfite genomic         sequencing PCR;         -   wherein the one or more genes is selected from one of the             following groups:         -   (i) BHLHE23_C, CALN1_A, CD1D, HOXA7_A, LOC100132891,             MAX.chr1.8277479-8277527, MAX.chr15.96889013-96889128,             NACAD, ATP6V1B1, BANK1, C17orf64, DLX4, EMX1_A, FOXP4, GP5,             ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148,             MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395,             MPZ, PRKCB, STX16_B UBTF, LOC100132891, ITPRIPL1, ABLIM1,             MAX.chr19.46379903-46380197, ZSCAN12, BHLHE23_D, CXCL12,             KCNK9, OTX1, RIC3, SCRT2_B, MAX.chr17.73073682-73073814,             CDH4_E, HNF1B_B, TRH_A, MAX.chr20.1784209-1784461,             MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725,             BEST4, and DSCR6;         -   (ii) MAX.chr15.96889013-96889128, ATP6V1B1, C17orf64,             ITPRIPL1, MAX.chr11.14926602-14927148,             MAX.chr5.42994866-42994936, LOC100132891, ITPRIPL1, ABLIM1,             MAX.chr19.46379903-46380197, COL23A1, LAYN, OTX1, TRH_A,             MAX.chr5.145725410-145725459, and             MAX.chr11.68622869-68622968;         -   (iii) ATP6V1B1, MAX.chr11.14926602-14927148, PRKCB, TRH_A,             MPZ, GP5, TRIM67, MAX.chr12.4273906-4274012, CALN1_A,             MAX.chr12.4273906-4274012, MAX.chr5.42994866-42994936,             SCRT2_B, MAX.chr5.145725410-145725459, BHLHE23_D,             MAX.chr5.77268672-77268725, EMX1_A, DSCR6, and DLX4;         -   (iv) ATP6V1B1, LMX1B_A, BANK1, OTX1,             MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, GP5,             DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012,             CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B,             MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B,             MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968,             MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461,             LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197,             ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A,             CHST2_B, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, ABLIM1,             BHLHE23_D, ZSCAN12, GRASP, and C10orf125;         -   (v) ATP6V1B1, LMX1B_A, BANK1, OTX1, ST8SIA4,             MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ,             DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012,             CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B,             MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B,             MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968,             MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461,             LOC100132891, BHLHE23_D, ALOX5, MAX.chr19.46379903-46380197,             ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A,             CHST2_B, ITPRIPL1, IGF2BP3_B, CDH4_E, ABLIM1, SLC30A10,             C10orf125;         -   (vi) ATP6V1B1, LMX1B_A, BANK1, OTX1,             MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ,             DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012,             CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B,             MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B,             MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968,             MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461,             LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197,             CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A,             DSCR6, ITPRIPL1, IGF2BP3_B, CDH4_E, DLX4, ABLIM1, BHLHE23_D;             and         -   (vii) DSCR6, SCRT2_B, MPZ, MAX.chr8.124173030-124173395,             OSR2_A, MAX.chr11.68622869-68622968, ITPRIPL1,             MAX.chr5.145725410-145725459, BHLHE23_C, ITPRIPL1.

Preferably, the sensitivity for such methods is from about 70% to about 100%, or from about 80% to about 90%, or from about 80% to about 85%. Preferably, the specificity is from about 70% to about 100%, or from about 80% to about 90%, or from about 80% to about 85%.

Genomic DNA may be isolated by any means, including the use of commercially available kits. Briefly, wherein the DNA of interest is encapsulated in by a cellular membrane the biological sample must be disrupted and lysed by enzymatic, chemical or mechanical means. The DNA solution may then be cleared of proteins and other contaminants, e.g., by digestion with proteinase K. The genomic DNA is then recovered from the solution. This may be carried out by means of a variety of methods including salting out, organic extraction, or binding of the DNA to a solid phase support. The choice of method will be affected by several factors including time, expense, and required quantity of DNA. All clinical sample types comprising neoplastic matter or pre-neoplastic matter are suitable for use in the present method, e.g., cell lines, histological slides, biopsies, paraffin-embedded tissue, body fluids, stool, breast tissue, colonic effluent, urine, blood plasma, blood serum, whole blood, isolated blood cells, cells isolated from the blood, and combinations thereof.

The technology is not limited in the methods used to prepare the samples and provide a nucleic acid for testing. For example, in some embodiments, a DNA is isolated from a stool sample or from blood or from a plasma sample using direct gene capture, e.g., as detailed in U.S. Pat. Appl. Ser. No. 61/485,386 or by a related method.

The genomic DNA sample is then treated with at least one reagent, or series of reagents, that distinguishes between methylated and non-methylated CpG dinucleotides within at least one marker comprising a DMR (e.g., DMR 1-327, e.g., as provided by Table 2).

In some embodiments, the reagent converts cytosine bases which are unmethylated at the 5′-position to uracil, thymine, or another base which is dissimilar to cytosine in terms of hybridization behavior. However in some embodiments, the reagent may be a methylation sensitive restriction enzyme.

In some embodiments, the genomic DNA sample is treated in such a manner that cytosine bases that are unmethylated at the 5′ position are converted to uracil, thymine, or another base that is dissimilar to cytosine in terms of hybridization behavior. In some embodiments, this treatment is carried out with bisulfite (hydrogen sulfite, disulfite) followed by alkaline hydrolysis.

The treated nucleic acid is then analyzed to determine the methylation state of the target gene sequences (at least one gene, genomic sequence, or nucleotide from a marker comprising a DMR, e.g., at least one DMR chosen from DMR 1-327, e.g., as provided in Table 2). The method of analysis may be selected from those known in the art, including those listed herein, e.g., QuARTS and MSP as described herein.

Aberrant methylation, more specifically hypermethylation of a marker comprising a DMR (e.g., DMR 1-327, e.g., as provided by Table 2) is associated with a breast cancer.

The technology relates to the analysis of any sample associated with a breast cancer. For example, in some embodiments the sample comprises a tissue and/or biological fluid obtained from a patient. In some embodiments, the sample comprises a secretion. In some embodiments, the sample comprises blood, serum, plasma, gastric secretions, pancreatic juice, a gastrointestinal biopsy sample, microdissected cells from a breast biopsy, and/or cells recovered from stool. In some embodiments, the sample comprises breast tissue. In some embodiments, the subject is human. The sample may include cells, secretions, or tissues from the breast, liver, bile ducts, pancreas, stomach, colon, rectum, esophagus, small intestine, appendix, duodenum, polyps, gall bladder, anus, and/or peritoneum. In some embodiments, the sample comprises cellular fluid, ascites, urine, feces, pancreatic fluid, fluid obtained during endoscopy, blood, mucus, or saliva. In some embodiments, the sample is a stool sample. In some embodiments, the sample is a breast tissue sample.

Such samples can be obtained by any number of means known in the art, such as will be apparent to the skilled person. For instance, urine and fecal samples are easily attainable, while blood, ascites, serum, or pancreatic fluid samples can be obtained parenterally by using a needle and syringe, for instance. Cell free or substantially cell free samples can be obtained by subjecting the sample to various techniques known to those of skill in the art which include, but are not limited to, centrifugation and filtration. Although it is generally preferred that no invasive techniques are used to obtain the sample, it still may be preferable to obtain samples such as tissue homogenates, tissue sections, and biopsy specimens

In some embodiments, the technology relates to a method for treating a patient (e.g., a patient with breast cancer, with early stage breast cancer, or who may develop breast cancer) (e.g., a patient with one or more of triple negative breast cancer, HER2⁺ breast cancer, Luminal A breast cancer, Luminal B breast cancer, BRCA1 breast cancer, BRCA2 breast cancer), the method comprising determining the methylation state of one or more DMR as provided herein and administering a treatment to the patient based on the results of determining the methylation state. The treatment may be administration of a pharmaceutical compound, a vaccine, performing a surgery, imaging the patient, performing another test. Preferably, said use is in a method of clinical screening, a method of prognosis assessment, a method of monitoring the results of therapy, a method to identify patients most likely to respond to a particular therapeutic treatment, a method of imaging a patient or subject, and a method for drug screening and development.

In some embodiments of the technology, a method for diagnosing a breast cancer in a subject is provided. The terms “diagnosing” and “diagnosis” as used herein refer to methods by which the skilled artisan can estimate and even determine whether or not a subject is suffering from a given disease or condition or may develop a given disease or condition in the future. The skilled artisan often makes a diagnosis on the basis of one or more diagnostic indicators, such as for example a biomarker (e.g., a DMR as disclosed herein), the methylation state of which is indicative of the presence, severity, or absence of the condition.

Along with diagnosis, clinical cancer prognosis relates to determining the aggressiveness of the cancer and the likelihood of tumor recurrence to plan the most effective therapy. If a more accurate prognosis can be made or even a potential risk for developing the cancer can be assessed, appropriate therapy, and in some instances less severe therapy for the patient can be chosen. Assessment (e.g., determining methylation state) of cancer biomarkers is useful to separate subjects with good prognosis and/or low risk of developing cancer who will need no therapy or limited therapy from those more likely to develop cancer or suffer a recurrence of cancer who might benefit from more intensive treatments.

As such, “making a diagnosis” or “diagnosing”, as used herein, is further inclusive of determining a risk of developing cancer or determining a prognosis, which can provide for predicting a clinical outcome (with or without medical treatment), selecting an appropriate treatment (or whether treatment would be effective), or monitoring a current treatment and potentially changing the treatment, based on the measure of the diagnostic biomarkers (e.g., DMR) disclosed herein. Further, in some embodiments of the presently disclosed subject matter, multiple determination of the biomarkers over time can be made to facilitate diagnosis and/or prognosis. A temporal change in the biomarker can be used to predict a clinical outcome, monitor the progression of breast cancer, and/or monitor the efficacy of appropriate therapies directed against the cancer. In such an embodiment for example, one might expect to see a change in the methylation state of one or more biomarkers (e.g., DMR) disclosed herein (and potentially one or more additional biomarker(s), if monitored) in a biological sample over time during the course of an effective therapy.

The presently disclosed subject matter further provides in some embodiments a method for determining whether to initiate or continue prophylaxis or treatment of a cancer in a subject. In some embodiments, the method comprises providing a series of biological samples over a time period from the subject; analyzing the series of biological samples to determine a methylation state of at least one biomarker disclosed herein in each of the biological samples; and comparing any measurable change in the methylation states of one or more of the biomarkers in each of the biological samples. Any changes in the methylation states of biomarkers over the time period can be used to predict risk of developing cancer, predict clinical outcome, determine whether to initiate or continue the prophylaxis or therapy of the cancer, and whether a current therapy is effectively treating the cancer. For example, a first time point can be selected prior to initiation of a treatment and a second time point can be selected at some time after initiation of the treatment. Methylation states can be measured in each of the samples taken from different time points and qualitative and/or quantitative differences noted. A change in the methylation states of the biomarker levels from the different samples can be correlated with breast cancer risk, prognosis, determining treatment efficacy, and/or progression of the cancer in the subject.

In preferred embodiments, the methods and compositions of the invention are for treatment or diagnosis of disease at an early stage, for example, before symptoms of the disease appear. In some embodiments, the methods and compositions of the invention are for treatment or diagnosis of disease at a clinical stage.

As noted, in some embodiments, multiple determinations of one or more diagnostic or prognostic biomarkers can be made, and a temporal change in the marker can be used to determine a diagnosis or prognosis. For example, a diagnostic marker can be determined at an initial time, and again at a second time. In such embodiments, an increase in the marker from the initial time to the second time can be diagnostic of a particular type or severity of cancer, or a given prognosis. Likewise, a decrease in the marker from the initial time to the second time can be indicative of a particular type or severity of cancer, or a given prognosis. Furthermore, the degree of change of one or more markers can be related to the severity of the cancer and future adverse events. The skilled artisan will understand that, while in certain embodiments comparative measurements can be made of the same biomarker at multiple time points, one can also measure a given biomarker at one time point, and a second biomarker at a second time point, and a comparison of these markers can provide diagnostic information.

As used herein, the phrase “determining the prognosis” refers to methods by which the skilled artisan can predict the course or outcome of a condition in a subject. The term “prognosis” does not refer to the ability to predict the course or outcome of a condition with 100% accuracy, or even that a given course or outcome is predictably more or less likely to occur based on the methylation state of a biomarker (e.g., a DMR). Instead, the skilled artisan will understand that the term “prognosis” refers to an increased probability that a certain course or outcome will occur; that is, that a course or outcome is more likely to occur in a subject exhibiting a given condition, when compared to those individuals not exhibiting the condition. For example, in individuals not exhibiting the condition (e.g., having a normal methylation state of one or more DMR), the chance of a given outcome (e.g., suffering from a breast cancer) may be very low.

In some embodiments, a statistical analysis associates a prognostic indicator with a predisposition to an adverse outcome. For example, in some embodiments, a methylation state different from that in a normal control sample obtained from a patient who does not have a cancer can signal that a subject is more likely to suffer from a cancer than subjects with a level that is more similar to the methylation state in the control sample, as determined by a level of statistical significance. Additionally, a change in methylation state from a baseline (e.g., “normal”) level can be reflective of subject prognosis, and the degree of change in methylation state can be related to the severity of adverse events. Statistical significance is often determined by comparing two or more populations and determining a confidence interval and/or a p value. See, e.g., Dowdy and Wearden, Statistics for Research, John Wiley & Sons, New York, 1983, incorporated herein by reference in its entirety. Exemplary confidence intervals of the present subject matter are 90%, 95%, 97.5%, 98%, 99%, 99.5%, 99.9% and 99.99%, while exemplary p values are 0.1, 0.05, 0.025, 0.02, 0.01, 0.005, 0.001, and 0.0001.

In other embodiments, a threshold degree of change in the methylation state of a prognostic or diagnostic biomarker disclosed herein (e.g., a DMR) can be established, and the degree of change in the methylation state of the biamarker in a biological sample is simply compared to the threshold degree of change in the methylation state. A preferred threshold change in the methylation state for biomarkers provided herein is about 5%, about 10%, about 15%, about 20%, about 25%, about 30%, about 50%, about 75%, about 100%, and about 150%. In yet other embodiments, a “nomogram” can be established, by which a methylation state of a prognostic or diagnostic indicator (biomarker or combination of biomarkers) is directly related to an associated disposition towards a given outcome. The skilled artisan is acquainted with the use of such nomograms to relate two numeric values with the understanding that the uncertainty in this measurement is the same as the uncertainty in the marker concentration because individual sample measurements are referenced, not population averages.

In some embodiments, a control sample is analyzed concurrently with the biological sample, such that the results obtained from the biological sample can be compared to the results obtained from the control sample. Additionally, it is contemplated that standard curves can be provided, with which assay results for the biological sample may be compared. Such standard curves present methylation states of a biomarker as a function of assay units, e.g., fluorescent signal intensity, if a fluorescent label is used. Using samples taken from multiple donors, standard curves can be provided for control methylation states of the one or more biomarkers in normal tissue, as well as for “at-risk” levels of the one or more biomarkers in tissue taken from donors with metaplasia or from donors with a breast cancer. In certain embodiments of the method, a subject is identified as having metaplasia upon identifying an aberrant methylation state of one or more DMR provided herein in a biological sample obtained from the subject. In other embodiments of the method, the detection of an aberrant methylation state of one or more of such biomarkers in a biological sample obtained from the subject results in the subject being identified as having cancer.

The analysis of markers can be carried out separately or simultaneously with additional markers within one test sample. For example, several markers can be combined into one test for efficient processing of a multiple of samples and for potentially providing greater diagnostic and/or prognostic accuracy. In addition, one skilled in the art would recognize the value of testing multiple samples (for example, at successive time points) from the same subject. Such testing of serial samples can allow the identification of changes in marker methylation states over time. Changes in methylation state, as well as the absence of change in methylation state, can provide useful information about the disease status that includes, but is not limited to, identifying the approximate time from onset of the event, the presence and amount of salvageable tissue, the appropriateness of drug therapies, the effectiveness of various therapies, and identification of the subject's outcome, including risk of future events.

The analysis of biomarkers can be carried out in a variety of physical formats. For example, the use of microtiter plates or automation can be used to facilitate the processing of large numbers of test samples. Alternatively, single sample formats could be developed to facilitate immediate treatment and diagnosis in a timely fashion, for example, in ambulatory transport or emergency room settings.

In some embodiments, the subject is diagnosed as having a breast cancer if, when compared to a control methylation state, there is a measurable difference in the methylation state of at least one biomarker in the sample. Conversely, when no change in methylation state is identified in the biological sample, the subject can be identified as not having breast cancer, not being at risk for the cancer, or as having a low risk of the cancer. In this regard, subjects having the cancer or risk thereof can be differentiated from subjects having low to substantially no cancer or risk thereof. Those subjects having a risk of developing a breast cancer can be placed on a more intensive and/or regular screening schedule, including endoscopic surveillance. On the other hand, those subjects having low to substantially no risk may avoid being subjected to additional testing for breast cancer (e.g., invasive procedure), until such time as a future screening, for example, a screening conducted in accordance with the present technology, indicates that a risk of breast cancer has appeared in those subjects.

As mentioned above, depending on the embodiment of the method of the present technology, detecting a change in methylation state of the one or more biomarkers can be a qualitative determination or it can be a quantitative determination. As such, the step of diagnosing a subject as having, or at risk of developing, a breast cancer indicates that certain threshold measurements are made, e.g., the methylation state of the one or more biomarkers in the biological sample varies from a predetermined control methylation state. In some embodiments of the method, the control methylation state is any detectable methylation state of the biomarker. In other embodiments of the method where a control sample is tested concurrently with the biological sample, the predetermined methylation state is the methylation state in the control sample. In other embodiments of the method, the predetermined methylation state is based upon and/or identified by a standard curve. In other embodiments of the method, the predetermined methylation state is a specifically state or range of state. As such, the predetermined methylation state can be chosen, within acceptable limits that will be apparent to those skilled in the art, based in part on the embodiment of the method being practiced and the desired specificity, etc.

Further with respect to diagnostic methods, a preferred subject is a vertebrate subject. A preferred vertebrate is warm-blooded; a preferred warm-blooded vertebrate is a mammal. A preferred mammal is most preferably a human. As used herein, the term “subject” includes both human and animal subjects. Thus, veterinary therapeutic uses are provided herein. As such, the present technology provides for the diagnosis of mammals such as humans, as well as those mammals of importance due to being endangered, such as Siberian tigers; of economic importance, such as animals raised on farms for consumption by humans; and/or animals of social importance to humans, such as animals kept as pets or in zoos. Examples of such animals include but are not limited to: carnivores such as cats and dogs; swine, including pigs, hogs, and wild boars; ruminants and/or ungulates such as cattle, oxen, sheep, giraffes, deer, goats, bison, and camels; and horses. Thus, also provided is the diagnosis and treatment of livestock, including, but not limited to, domesticated swine, ruminants, ungulates, horses (including race horses), and the like.

The presently-disclosed subject matter further includes a system for diagnosing a breast cancer and/or a specific form of breast cancer (e.g., triple negative breast cancer, HER2⁺ breast cancer, Luminal A breast cancer, Luminal B breast cancer, BRCA1 breast cancer, BRCA2 breast cancer) in a subject. The system can be provided, for example, as a commercial kit that can be used to screen for a risk of breast cancer or diagnose a breast cancer in a subject from whom a biological sample has been collected. An exemplary system provided in accordance with the present technology includes assessing the methylation state of a DMR as provided in Table 2.

EXAMPLES Example I

This example describes the discovery and tissue validation of breast-cancer specific markers.

Table 1 shows the number of tissue samples for each subtype of breast cancer used in the discovery of breast cancer specific markers.

TABLE 1 Breast Cancer Subtype Number of Subjects Total Basal-like/Triple Negative 18 18 HER2⁺ 18 18 Luminal A 18 18 Luminal B 18 18 BRCA 1 6 15 BRCA 2 9 Normal Breast 18 45 Normal Breast + BRCA 9 Normal Buffy Coat 18

For discovery of methylation markers by RRBS, frozen tissue samples were obtained from 72 invasive breast cancer cases (18 luminal A, 18 luminal B, 18 basal-like/triple negative, and 18 HER2+), 15 invasive breast cancer from BRCA germline mutation patients (6 BRCA1, 9 BRCA2), and 45 controls (18 normal breast (reduction mammoplasty or prophylactic mastectomy, 9 histologically normal breast in germline BRCA carriers (prophylactic mastectomy), and 18 normal buffy coat)). Tumor and breast tissue sections were reviewed by an expert GI pathologist to confirm diagnosis and estimate abnormal cellularity. Sections were then macro-dissected. Genomic DNA was purified using the QiaAmp Mini kit (Qiagen, Valencia Calif.). DNA (300 ng) was fragmented by digestion with 10 Units of MspI. Digested fragments were end-repaired and A-tailed with 5 Units of Klenow fragment (3′-5′ exo-), and ligated overnight to methylated TruSeq adapters (Illumina, San Diego Calif.) containing barcode sequences (to link each fragment to its sample ID.) Reactions were purified using AMPure XP SPRI beads/buffer (Beckman Coulter, Brea Calif.).

Tissue samples then underwent bisulfite conversion (twice) using a modified EpiTect protocol (Qiagen). qPCR (LightCycler 480—Roche, Mannheim Germany) was used to determine the optimal enrichment Ct. The following conditions were used for final enrichment PCR: Each 50 uL reaction contained 5 uL of 10× buffer, 1.25 uL of 10 mM each deoxyribonucleotide triphosphate (dNTP), 5 uL primer cocktail (˜5 uM), 15 uL template (sample), 1 uL PfuTurbo Cx hotstart (Agilent, Santa Clara Calif.) and 22.75 water; temperatures and times were 95 C-5 min; 98 C-30 sec; 16 cycles of 98 C-10 sec, 65 C-30 sec, 72 C-30 sec, 72 C-5 min and 4 C hold, respectively. Samples were SPRI bead purified and then tested on the Bioanalyzer 2100 (Agilent) to assess the DNA size distribution of the enrichment. Size selection of 160-520 bp fragments (40-400 bp inserts) was performed using AMPure XP SPRI beads/buffer (Beckman Coulter, Brea Calif.). Buffer cutoffs were 0.7×-1.1× sample volumes. Samples were combined (equimolar) into 4-plex libraries based on the randomization scheme and tested with the bioanalyzer for final size and concentration verification, and with qPCR (KAPA Library Quantification Kit—KAPA Biosystems, Cape Town South Africa).

Tissue samples were loaded onto single read flow cells according to a randomized lane assignment and sequencing was performed by the Next Generation Sequencing Core at the Mayo Clinic Medical Genome Facility on the Illumina HiSeq 2000 platform. Reads were unidirectional for 101 cycles. The standard Illumina pipeline was run for the primary analysis. SAAP-RRBS (streamlined analysis and annotation pipeline for reduced representation bisulfite sequencing) was used for quality scoring, sequence alignment, annotation, and methylation extraction.

Breast cancer tissue yielded large numbers of discriminate DMRs, many of which had not been identified before. Comparing the methylation of breast cancer tissue samples to normal breast tissue, 327 methylated regions were identified (see, Table 2) that distinguished breast cancer tissue from normal breast tissue (the genomic coordinates for the regions shown in Table 2 are based on the Human February 2009 (GRCh37/hg19) Assembly). Table 3 shows 48 methylated regions that distinguished triple negative breast cancer tissue from normal breast tissue. Table 4 shows 122 methylated regions that distinguished HER2⁺ breast cancer tissue from normal breast tissue. Table 5 shows 75 methylated regions that distinguished Luminal A breast cancer tissue from normal breast tissue. Table 6 shows 39 methylated regions that distinguished Luminal B breast cancer tissue from normal breast tissue. Table 7 shows 49 methylated regions that distinguished BRCA1 breast cancer tissue from normal breast tissue. Table 8 shows 45 methylated regions that distinguished BRCA2 breast cancer tissue from normal breast tissue. Table 9 shows 21 methylated regions that distinguished invasive breast cancer tissue from normal breast tissue.

TABLE 2 Identified methylated regions distinguishing breast cancer tissue from normal breast tissue. DMR Region on Chromosome No. Gene Annotation (starting base-ending base) 1 ZSCAN23 chr6: 28411152-28411272 2 AADAT.R chr4: 171010951-171010991 3 ABLIM1 chr10: 116391588-116391793 4 ACCN1 chr17: 31620207-31620314 5 AFAP1L1 chr5: 148651161-148651242 6 AJAP1_A chr1: 4715535-4715646 7 AJAP1_B chr1: 4715931-4716021 8 AKR1B1 chr7: 134143171-134143684 9 ALOX5 chr10: 45914840-45914949 10 AMN chr14: 103394920-103395019 11 ANPEP chr15: 90358420-90358514 12 ANTXR2 chr4: 80993475-80993634 13 ARL5C chr17: 37321515-37321626 14 ASCL2 chr11: 2292240-2292361 15 ATP6V1B1 chr2: 71192354-71192453 16 B3GNT5 chr3: 182971589-182971825 17 BANK1 chr4: 102711871-102712076 18 BCAT1 chr12: 25055906-25055975 19 BEGAIN chr14: 101033665-101033813 20 BEST4 chr1: 45251853-45252029 21 BHLHE23_A chr20: 61637950-61637986 22 BHLHE23_B chr20: 61638020-61638083 23 BHLHE23_C chr20: 61638088-61638565 24 BHLHE23_D chr20: 61638244-61638301 25 BMP4 chr14: 54421578-54421916 26 BMP6 chr6: 7727566-7727907 27 C10orf125 chr10: 135171410-135171504 28 C10orf93 chr10: 134756078-134756167 29 Cl7orf64 chr17: 58499095-58499190 30 C19orf35 chr19: 2282568-2282640 31 C19orf66 chr19: 10197688-10197823 32 C1QL2 chr2: 119916511-119916572 33 C20orf195_A chr20: 62185293-62185364 34 C20orf195_B chr20: 62185418-62185546 35 C7orf52 chr7: 100823483-100823514 36 CALN1_A chr7: 71801486-71801594 37 CALN1_B chr7: 71801741-71801800 38 CAMKV chr3: 49907259-49907298 39 CAPN2.FR chr1: 223900347-223900405 40 CAV2 chr7: 116140205-116140342 41 CBLN1_A chr16: 49315588-49315691 42 CBLN1_B chr16: 49316198-49316258 43 CCDC61 chr19: 46519467-46519536 44 CCND2_A chr12: 4378317-4378375 45 CCND2_B chr12: 4380560-4380681 46 CCND2_C chr12: 4384096-4384146 47 CD1D chr1: 158150864-158151129 48 CD8A chr2: 87017780-87017917 49 CDH4_A chr20: 59827230-59827285 50 CDH4_B chr20: 59827762-59827776 51 CDH4_C chr20: 59827794-59827868 52 CDH4_D chr20: 59828193-59828258 53 CDH4_E chr20: 59828479-59828729 54 CDH4_F chr20: 59828778-59828814 55 CHRNA7 chr15: 32322830-32322897 56 CHST2_A chr3: 142838025-142838494 57 CHST2_B chr3: 142839223-142839568 58 CLIC6 chr21: 36042025-36042131 59 CLIP4 chr2: 29338109-29338339 60 COL23A1.R chr5: 178017669-178017854 61 CR1 chr1: 207669481-207669639 62 CRHBP chr5: 76249939-76249997 63 CXCL12.F chr10: 44881210-44881300 64 DBNDD1.FR chr16: 90085625-90085681 65 DLK1 chr14: 101193295-101193318 66 DLX4 chr17: 48042562-48042606 67 DLX6 chr7: 96635255-96635475 68 DNAJC6 chr1: 65731412-65731507 69 DNM3_A chr1: 171810393-171810575 70 DNM3_B chr1: 171810648-171810702 71 DNM3_C chr1: 171810806-171810920 72 DSCR6 chr21: 38378540-38378601 73 DTX1 chr12: 113515535-113515637 74 EMX1_A chr2: 73151498-73151578 75 EMX1_B chr2: 73151663-73151756 76 EPHA4 chr2: 222436217-222436320 77 ESPN chr1: 6508784-6509175 78 ESYT3 chr3: 138153979-138154071 79 ETS1_A chr11: 128391809-128391908 80 ETS1_B chr11: 128392062-128392309 81 FABP5 chr8: 82192605-82192921 82 FAIM2 chr12: 50297863-50297988 83 FAM126A chr7: 23053941-23054066 84 FAM1290.F chr19: 17650551-17650610 85 FAM150A chr8: 53478266-53478416 86 FAM150B chr2: 287868-287919 87 FAM171A1 chr10: 15412558-15412652 88 FAM189A1 chr15: 29862130-29862169 89 FAM20A chr17: 66597237-66597326 90 FAM59B chr2: 26407713-26407972 91 FBN1 chr15: 48937412-48937541 92 FLJ42875 chr1: 2987037-2987116 93 FLRT2 chr14: 85998469-85998535 94 FMN2 chr1: 240255171-240255253 95 FMNL2 chr2: 153192734-153192836 96 FOXP4 chr6: 41528816-41528958 97 FSCN1 chr7: 5633506-5633615 98 GAD2 chr10: 26505066-26505385 99 GAS7 chr17: 10101325-10101397 100 GCGR chr17: 79761970-79762088 101 GLI3 chr7: 42267808-42267899 102 GLP1R chr6: 39016381-39016421 103 GNG4 chr1: 235813658-235813798 104 GPS chr3: 194118738-194118924 105 GRASP chr12: 52400919-52401166 106 GRM7 chr3: 6902873-6902931 107 GSTP1 chr11: 67350986-67351055 108 GYPC_A chr2: 127413505-127413678 109 GYPC_B chr2: 127414096-127414189 110 HAND2 chr4: 174450452-174450478 111 HBM chr16: 216426-216451 112 HESS chr1: 2461823-2461915 113 HHEX.F chr10: 94449486-94449597 114 HMGA2 chr12: 66219385-66219487 115 HNF1B_A chr17: 36103713-36103793 116 HNF1B_B chr17: 36105390-36105448 117 HOXA1_A chr7: 27135603-27135889 118 HOXA1_B chr7: 27136191-27136244 119 HOXA7_A chr7: 27195742-27195895 120 HOXA7_B chr7: 27196032-27196190 121 HOXA7_C chr7: 27196441-27196531 122 HOXD9 chr2: 176987716-176987739 123 IGF2BP3_A chr7: 23508901-23509225 124 IGF2BP3_B chr7: 23513817-23514114 125 IGFBP5 chr2: 217559103-217559244 126 IGSF9B_A chr11: 133825409-133825476 127 IGSF9B_B chr11: 133825491-133825530 128 IL15RA chr10: 6018610-6018848 129 IL17REL chr22: 50453462-50453555 130 INSM1 chr20: 20348140-20348182 131 ITGA9 chr3: 37493895-37493994 132 ITPKA_A chr15: 41787438-41787784 133 ITPKA_B chr15: 41793928-41794003 134 ITPRIPL1 chr2: 96990968-96991328 135 JSRP1 chr19: 2253163-2253376 136 KCNA1 chr12: 5019401-5019633 137 KCNE3 chr11: 74178260-74178346 138 KCNH8 chr3: 19189837-19189897 139 KCNK17_A chr6: 39281195-39281282 140 KCNK17_B chr6: 39281408-39281478 141 KCNK9.FR chr8: 140715096-140715164 142 KCNQ2 chr20: 62103558-62103625 143 KIAA1949 chr6: 30646976-30647084 144 KIRREL2 chr19: 36347825-36347863 145 KLF16 chr19: 1857330-1857476 146 KLHDC7B chr22: 50987219-50987304 147 LAYN.R chr11: 111412023-111412074 148 LIME1 chr20: 62369116-62369393 149 LMX1B_A chr9: 129388175-129388223 150 LMX1B_B chr9: 129388231-129388495 151 LMX1B_C chr9: 129445588-129445603 152 LOC100131176 chr7: 151106986-151107060 153 LOC100132891 chr8: 72755897-72756295 154 LOC100302401.R chr1: 178063509-178063567 155 LOC283999 chr17: 76227905-76227960 156 LRRC34 chr3: 169530006-169530139 157 LSS.F chr21: 47649525-47649615 158 LY6H chr8: 144241547-144241557 159 MAGI2 chr7: 79083359-79083600 160 MAST1 chr19: 12978399-12978642 161 MAX.chr1.158083198-158083476 chr1: 158083198-158083476 162 MAX.chr1.228074764-228074977 chr1: 228074764-228074977 163 MAX.chr1.239549742-239549886 chr1: 239549742-239549886 164 MAX.chr1.46913931-46913950 chr1: 46913931-46913950 165 MAX.chr1.8277285-8277316 chr1: 8277285-8277316 166 MAX.chr1.8277479-8277527 chr1: 8277479-8277527 167 MAX.chr10.130085265-130085312 chr10: 130085265-130085312 168 MAX.chr11.14926602-14927148 chr11: 14926602-14927148 169 MAX.chr11.68622869-68622968 chr11: 68622869-68622968 170 MAX.chr12.4273906-4274012 chr12: 4273906-4274012 171 MAX.chr12.59990591-59990895 chr12: 59990591-59990895 172 MAX.chr14.101176106-101176260 chr14: 101176106-101176260 173 MAX.chr15.96889013-96889128 chr15: 96889013-96889128 174 MAX.chr17.73073682-73073814 chr17: 73073682-73073814 175 MAX.chr17.8230197-8230314 chr17: 8230197-8230314 176 MAX.chr18.5629721-5629791 chr18: 5629721-5629791 177 MAX.chr18.76734362-76734476 chr18: 76734362-76734476 178 MAX.chr19.30719261-30719354 chr19: 30719261-30719354 179 MAX.chr19.46379903-46380197 chr19: 46379903-46380197 180 MAX.chr2.223183057-223183114.FR chr2: 223183057-223183114 181 MAX.chr2.238864674-238864735 chr2: 238864674-238864735 182 MAX.chr2.97193163-97193287 chr2: 97193163-97193287 183 MAX.chr2.97193478-97193562 chr2: 97193478-97193562 184 MAX.chr20.1783841-1784054 chr20: 1783841-1784054 185 MAX.chr20.1784209-1784461 chr20: 1784209-1784461 186 MAX.chr21.44782441-44782498 chr21: 44782441-44782498 187 MAX.chr21.47063802-47063851 chr21: 47063802-47063851 188 MAX.chr22.23908718-23908782 chr22: 23908718-23908782 189 MAX.chr22.42679578-42679917 chr22: 42679578-42679917 190 MAX.chr4.8859253-8859329 chr4: 8859253-8859329 191 MAX.chr4.8859602-8859669 chr4: 8859602-8859669 192 MAX.chr4.8860002-8860038 chr4: 8860002-8860038 193 MAX.chr5.145725410-145725459 chr5: 145725410-145725459 194 MAX.chr5.172234248-172234494 chr5: 172234248-172234494 195 MAX.chr5.178957564-178957598 chr5: 178957564-178957598 196 MAX.chr5.180101084-180101094 chr5: 180101084-180101094 197 MAX.chr5.42952185-42952280 chr5: 42952185-42952280 198 MAX.chr5.42994866-42994936 chr5: 42994866-42994936 199 MAX.chr5.77268672-77268725 chr5: 77268672-77268725 200 MAX.chr5.81148300-81148332 chr5: 81148300-81148332 201 MAX.chr6.108440684-108440788 chr6: 108440684-108440788 202 MAX.chr6.130686865-130686985 chr6: 130686865-130686985 203 MAX.chr6.157556793-157556856 chr6: 157556793-157556856 204 MAX.chr6.157557371-157557657 chr6: 157557371-157557657 205 MAX.chr6.27064703-27064783 chr6: 27064703-27064783 206 MAX.chr7.151145632-151145743 chr7: 151145632-151145743 207 MAX.chr7.152622607-152622638 chr7: 152622607-152622638 208 MAX.chr8.124173030-124173395 chr8: 124173030-124173395 209 MAX.chr8.124173128-124173268 chr8: 124173128-124173268 210 MAX.chr8.143533298-143533558 chr8: 143533298-143533558 211 MAX.chr8.145104132-145104218 chr8: 145104132-145104218 212 MAX.chr8.687688-687736 chr8: 687688-687736 213 MAX.chr8.688863-688924 chr8: 688863-688924 214 MAX.chr9.114010-114207 chr9: 114010-114207 215 MAX.chr9.136474504-136474527 chr9: 136474504-136474527 216 MCF2L2 chr3: 182896930-182897245 217 MERTK chr2: 112656676-112656744 218 MGAT1 chr5: 180230434-180230767 219 MIB2 chr1: 1565891-1565987 220 MN1 chr22: 28197962-28198388 221 MPZ chr1: 161275561-161275996 222 MSX2P1 chr17: 56234436-56234516 223 NACAD chr7: 45128502-45128717 224 NID2_A chr14: 52535260-52535353 225 NID2_B chr14: 52535974-52536161 226 NID2_C chr14: 52536192-52536328 227 NKX2-6 chr8: 23564115-23564146 228 NR2F6 chr19: 17346428-17346459 229 NTRK3 chr15: 88800287-88800414 230 NXPH4 chr12: 57618904-57618944 231 ODC1 chr2: 10589075-10589243 232 OLIG3_A chr6: 137818896-137818917 233 OLIG3_B chr6: 137818978-137818988 234 OSR2_A chr8: 99952233-99952366 235 OSR2_B chr8: 99952801-99952919 236 OSR2_C chr8: 99960580-99960630 237 OTX1.R chr2: 63281481-63281599 238 PAQR6 chr1: 156215470-156215739 239 PCDH8 chr13: 53421299-53421322 240 PDX1 chr13: 28498503-28498544 241 PDXK_A chr21: 45148429-45148556 242 PDXK_B chr21: 45148575-45148681 243 PEAR1 chr1: 156863318-156863493 244 PIF1 chr15: 65116285-65116597 245 PLXNC1_A chr12: 94544327-94544503 246 PLXNC1_B chr12: 94544333-94544426 247 POU4F1 chr13: 79177505-79177532 248 PPARA chr22: 46545328-46545457 249 PPARG chr3: 12330042-12330152 250 PPP1R16B_A chr20: 37435507-37435716 251 PPP1R16B_B chr20: 37435738-37435836 252 PPP2R5C chr14: 102247681-102247929 253 PRDM13_A chr6: 100061616-100061742 254 PRDM13_B chr6: 100061748-100061792 255 PRHOXNB chr13: 28552424-28552562 256 PRKCB chr16: 23847575-23847699 257 PRMT1 chr19: 50179501-50179635 258 PROM1 chr4: 16084793-16085112 259 PTPRM chr18: 7568565-7568808 260 PTPRN2 chr7: 157483341-157483429 261 RASGRF2 chr5: 80256117-80256162 262 RBFOX3_A chr17: 77179579-77179752 263 RBFOX3_B chr17: 77179778-77180064 264 RFX8 chr2: 102090934-102091130 265 RGS17 chr6: 153452120-153452393 266 RIC3.F chr11: 8190622-8190711 267 RIPPLY2 chr6: 84563228-84563287 268 RYR2_A chr1: 237205369-237205428 269 RYR2_B chr1: 237205619-237205640 270 SALL3 chr18: 76739321-76739404 271 SBNO2 chr19: 1131795-1131992 272 SCRT2_A chr20: 644533-644618 273 SCRT2_B chr20: 644573-644618 274 SERPINB9_A chr6: 2902941-2902998 275 SERPINB9_B chr6: 2903031-2903143 276 SLC16A3.F chr17: 80189895-80189962 277 SLC22A20.FR chr11: 64993239-64993292 278 SLC2A2 chr3: 170746149-170746208 279 SLC30A10 chr1: 220101458-220101634 280 SLC7A4 chr22: 21386780-21386831 281 SLC8A3 chr14: 70654596-70654640 282 SLITRK5.R chr13: 88329960-88330076 283 SNCA chr4: 90758071-90758118 284 SPHK2 chr19: 49127580-49127683 285 ST8SIA4 chr5: 100240059-100240276 286 STAC2_A chr17: 37381217-37381303 287 STAC2_B chr17: 37381689-37381795 288 STX16_A chr20: 57224798-57224975 289 STX16_B chr20: 57225077-57225227 290 SYN2 chr3: 12045894-12045967 291 SYNJ2 chr6: 158402213-158402536 292 SYT5 chr19: 55690401-55690496 293 TALI chr1: 47697702-47697882 294 TBKBP1 chr17: 45772630-45772726 295 TBX1 chr22: 19754257-19754550 296 TEPP chr16: 58018790-58018831 297 TIMP2 chr17: 76921762-76921779 298 TLX1NB chr10: 102881178-102881198 299 TMEFF2 chr2: 193060012-193060126 300 TMEM176A chr7: 150497411-150497535 301 TNFRSF10D chr8: 23020896-23021114 302 TOX chr8: 60030723-60030754 303 TRH_A chr3: 129693484-129693575 304 TRH_B chr3: 129694457-129694501 305 TRIM67 chr1: 231297047-231297159 306 TRIM71_A chr3: 32858861-32858897 307 TRIM71_B chr3: 32859445-32859559 308 TRIM71_C chr3: 32860020-32860090 309 TSHZ3 chr19: 31839809-31840038 310 UBTF chr17: 42287924-42288018 311 ULBP1 chr6: 150285563-150285661 312 USP44_A chr12: 95942148-95942178 313 USP44_B chr12: 95942519-95942558 314 UTF1 chr10: 135044125-135044171 315 UTS2R chr17: 80329497-80329534 316 VIPR2 chr7: 158937370-158937481 317 VN1R2 chr19: 53758121-53758147 318 VSNL1 chr2: 17720216-17720257 319 VSTM2B_A chr19: 30016283-30016357 320 VSTM2B_B chr19: 30017789-30018165 321 ZBTB16 chr11: 113929882-113930166 322 ZFP64 chr20: 50721057-50721235 323 ZNF132 chr19: 58951402-58951775 324 ZNF486 chr19: 20278004-20278145 325 ZNF626 chr19: 20844070-20844199 326 ZNF671 chr19: 58238810-58238955 327 ZSCAN12 chr6: 28367128-28367509

TABLE 3 Table 3 shows 1) area under the curve for identified methylated regions distinguishing triple negative breast cancer tissue from normal breast tissue, 2) the Fold Change (FC) for triple negative breast cancer tissue vs. normal breast tissue, and 3) the Fold Change (FC) for triple negative breast cancer tissue vs. buffy coat (normal). Region on Chromosome (starting Gene Annotation base-ending base) AUC FC Tissue FC Buffy DMR ABLIM1 chr10:116391588-116391793 0.821 9.187127 6.095762 3 AJAP1_B chr1:4715931-4716021 0.9358 33.64347 55.12195 7 ASCL2 chr11:2292240-2292361 0.9479 21.93763 13.66322 14 ATP6V1B1 chr2:71192354-71192453 1 2.711325 92.96954 15 BANK1 chr4:102711871-102712076 1 1.43525 61.96732 17 CALN1_A chr7:71801486-71801594 0.9346 17.12541 17.09291 36 CALN1_B chr7:71801741-71801800 0.8742 19.87087 36.73595 37 CLIC6 chr21:36042025-36042131 1 3.059621 93.40228 58 DSCR6 chr21:38378540-38378601 0.9641 16.80192 23.82779 72 FOXP4 chr6:41528816-41528958 1 1.645757 >1 × 10⁶ 96 GAD2 chr10:26505066-26505385 0.9134 29.30865 44.14014 98 GCGR chr17:79761970-79762088 0.9506 15.57835 9.860312 100 GP5 chr3:194118738-194118924 0.9961 1.942734 122.3962 104 GRASP chr12:52400919-52401166 0.9506 34.60851 58.57791 105 HBM chr16:216426-216451 0.9389 28.44886 28.4872 111 HNF1B_B chr17:36105390-36105448 1 2.492725 20.57995 116 KLF16 chr19:1857330-1857476 0.8785 19.65243 148.6852 145 MAGI2 chr7:79083359-79083600 0.9306 16.79564 5.734084 159 MAX.chr11.14926602- chr11:14926602-14927148 1 3.891519 87.49446 168 14927148 MAX.chr12.4273906- chr12:4273906-4274012 0.9815 20.08783 149.5817 170 4274012 MAX.chr17.73073682- chr17:73073682-73073814 0.9883 1.679173 72.85714 174 73073814 MAX.chr18.76734362- chr18:76734362-76734370 0.9641 24.69328 77.26996 177 76734370 MAX.chr2.97193478- chr2:97193478-97193562 0.9167 22.01754 119.8408 183 97193562 MAX.chr22.42679578- chr22:42679578-42679917 0.9375 27.34823 20.78761 189 42679917 MAX.chr4.8859253- chr4:8859253-8859329 0.9346 13.7246 93.86646 190 8859329 MAX.chr4.8859602- chr4:8859602-8859669 0.9632 11.5 27.44798 191 8859669 MAX.chr4.8860002- chr4:8860002-8860038 0.9491 20.16179 84.79759 192 8860038 MAX.chr5.145725410- chr5:145725410-145725459 0.933 12.88169 25.65149 193 145725459 MAX.chr6.157557371- chr6:157557371-157557657 1 6.19614 35.10826 204 157557657 MPZ chr1:161275561-161275996 0.9504 20.73901 191.2216 221 NKX2-6 chr8:23564115-23564146 0.9583 18.63167 38.06928 227 PDX1 chr13:28498503-28498544 0.9657 18.77193 64.6598 240 PLXNC1_A chr12:94544327-94544503 0.9449 4.617089 38.86521 245 PPARG chr3:12330042-12330152 0.9259 30.22681 10.42603 249 PRKCB chr16:23847575-23847699 0.9281 20.45208 295.1076 256 PTPRN2 chr7:157483341-157483429 0.9281 12.35294 32.67167 260 RBFOX3_A chr17:77179579-77179752 0.9074 19.19924 18.24275 262 SCRT2_A chr20:644533-644618 0.9321 18.30644 7.92126 272 SLC7A4 chr22:21386780-21386831 0.9792 17.60673 23.649 280 STAC2_B chr17:37381689-37381795 0.9074 26.95157 73.07841 287 STX16_A chr20:57224798-57224975 1 1.36278 106.6599 288 STX16_B chr20:57225077-57225227 1 1.593456 198.3707 289 TBX1 chr22:19754257-19754550 0.8676 1.385844 35.45752 295 TRH_A chr3:129693484-129693575 1 3.188452 67.015 303 VSTM2B_A chr19:30016283-30016357 0.9246 27.51997 28.83311 319 ZBTB16 chr11:113929882-113930166 0.9003 18.82877 26.23126 321 ZNF132 chr19:58951402-58951775 0.9062 33.99015 85.56548 323 ZSCAN23 chr6:28411152-28411272 0.9163 20.33657 59.21927 1

TABLE 4 Table 4 shows 1) area under the curve for identified methylated regions distinguishing HER2⁺ breast cancer tissue from normal breast tissue, 2) the Fold Change (FC) for HER2⁺ breast cancer tissue vs. normal breast tissue, and 3) the Fold Change (FC) for HER2⁺ breast cancer tissue vs. buffy coat (normal). Region on Chromosome (starting base- Gene Annotation ending base) AUC FC Tissue FC Buffy DMR ABLIM1 chr10:116391588- 0.9846 20.96881 13.91304 3 116391793 AFAP1L1 chr5:148651161- 0.9902 19.53202 21.58802 5 148651242 AKR1B1 chr7:134143171- 0.9537 31.02981 91.43744 8 134143684 ALOX5 chr10:45914840- 0.9522 30.50987 110.198 9 45914949 AMN chr14:103394920- 0.951 23.99824 172.1942 10 103395019 ARL5C chr17:37321515- 0.9526 23.90438 76.38447 13 37321626 BANK1 chr4:102711871- 1 1.178479 50.88113 17 102712076 BCAT1 chr12:25055906- 0.9641 17.75806 73.18046 18 25055975 BEGAIN chr14:101033665- 1 25.33593 29.59147 19 101033813 BEST4 chr1:45251853- 0.9753 40.07491 76.68804 20 45252029 BHLHE23_B chr20:61638020- 0.9765 33.01942 26.19353 22 61638083 BHLHE23_C chr20:61638088- 0.9938 37.3359 51.54664 23 61638565 C17orf64 chr17:58499095- 0.9583 19.9771 281.2989 29 58499190 C1QL2 chr2:119916511- 1 20.92054 20.81967 32 119916572 C7orf52 chr7:100823483- 0.9967 34.66759 20.82363 35 100823514 CALN1_B chr7:71801741- 0.9444 17.5999 32.5375 37 71801800 CAV2 chr7:116140205- 0.9506 21.22966 20.87111 40 116140342 CD8A chr2:87017780- 0.9907 20 21.32184 48 87017917 CDH4_A chr20:59827230- 1 37.02782 42.86441 49 59827285 CDH4_B chr20:59827762- 0.9907 22.76012 30.46422 50 59827776 CDH4_C chr20:59827794- 1 24.72984 23.55503 51 59827868 CDH4_D chr20:59828193- 0.9958 25.09787 28.16619 52 59828258 CDH4_E chr20:59828479- 1 28.97206 36.79341 53 59828729 CDH4_F chr20:59828778- 0.9969 36.81109 34.35411 54 59828814 CHST2_B chr3:142839223- 1 34.72482 117.3308 57 142839568 CLIP4 chr2:29338109- 0.9739 20.94282 46.96947 59 29338339 CR1 chr1:207669481- 0.9691 28.25359 42.1256 61 207669639 DLK1 chr14:101193295- 0.9692 31.7083 30.33924 65 101193318 DNAJC6 chr1:65731412- 0.9691 35.40474 85.64082 68 65731507 DNM3_A chr1:171810393- 0.9506 16.78657 101.8429 69 171810575 EMX1_A chr2:73151498- 0.9923 14.73071 31.60031 74 73151578 ESPN chr1:6508784-6509175 1 7.096692 53.37799 77 FABP5 chr8:82192605- 0.9475 18.49851 297.5222 81 82192921 FAM150A chr8:53478266- 1 26.83744 30.32598 85 53478416 FLJ42875 chr1:2987037-2987116 0.9667 40.47655 36.2069 92 GLP1R chr6:39016381- 0.9725 22.49606 24.93019 102 39016421 GNG4 chr1:235813658- 0.9771 30.92768 28.97404 103 235813798 GYPC_A chr2:127413505- 0.9568 20.44592 91.04351 108 127413678 HAND2 chr4:174450452- 0.9804 15.73026 23.81474 110 174450478 HES5 chr1:2461823-2461915 0.9383 31.91815 23.13591 112 HNF1B_A chr17:36103713- 0.963 29.18949 39.45301 115 36103793 HNF1B_B chr17:36105390- 1 3.593578 29.6686 116 36105448 HOXA1_A chr7:27135603- 0.966 38.04738 137.2168 117 27135889 HOXA1_B chr7:27136191- 0.9522 33.78035 144.6796 118 27136244 HOXA7_A chr7:27195742- 0.9784 22.8203 34.64696 119 27195895 HOXA7_B chr7:27196032- 1 27.92413 23.54393 120 27196190 HOXA7_C chr7:27196441- 0.9896 20.14606 27.05282 121 27196531 HOXD9 chr2:176987716- 0.9926 21.14973 31.76069 122 176987739 IGF2BP3_A chr7:23508901- 0.9599 22.75591 108.9025 123 23509225 IGF2BP3_B chr7:23513817- 0.9853 8.970018 75.12555 124 23514114 IGSF9B_A chr11:133825409- 0.9691 13.84201 22.99205 126 133825476 IL15RA chr10:6018610- 0.941 6.854012 58.47407 128 6018848 INSM1 chr20:20348140- 0.9542 25.90248 26.65219 130 20348182 ITPKA_B chr15:41793928- 0.9686 21.34743 23.96879 133 41794003 ITPRIPL1 chr2:96990968- 0.963 31.10465 280.3382 134 96991328 KCNE3 chr11:74178260- 0.9529 37.65937 30.48685 137 74178346 KCNK17_B chr6:39281408- 0.966 31.5971 104.6458 140 39281478 LIME1 chr20:62369116- 1 3.213465 75.53068 148 62369393 LOC100132891 chr8:72755897- 0.9691 33.07259 53.92857 153 72756295 LOC283999 chr17:76227905- 0.9837 14.82154 37.5134 155 76227960 LY6H chr8:144241547- 0.9722 14.69706 28.21535 158 144241557 MAST1 chr19:12978399- 0.9654 26.7166 37.34729 160 12978642 MAX.chrl.158083198- chr1:158083198- 0.9907 35.99869 32.08705 161 158083476 158083476 MAX.chr1.228074764- chr1:228074764- 0.9846 33.58852 37.24138 162 228074977 228074977 MAX.chr1.46913931- chr1:46913931- 0.9784 27.23106 24.5654 164 46913950 46913950 MAX.chr10.130085265- chr10:130085265- 1 23.65531 23.42432 167 130085312 130085312 MAX.chr11.68622869- chr11:68622869- 1 72.19153 99.26843 169 68622968 68622968 MAX.chr14.101176106- chr14:101176106- 0.9771 19.13125 42.66797 172 101176260 101176260 MAX.chr15.96889013- chr15:96889069- 0.9882 16.95179 32.0494 173 96889128 96889128 MAX.chr17.8230197- chr1:8230197- 0.966 17.19388 40.39153 175 8230314 8230314 MAX.chr19.46379903- chr19:46379903- 0.9902 32.1749 31.74585 179 46380197 46380197 MAX.chr2.97193163- chr2:97193163- 0.9522 25.05757 666.7396 182 97193287 97193287 MAX.chr2.97193478- chr2:97193478- 0.9549 29.12281 158.5146 183 97193562 97193562 MAX.chr20.1784209- chr20:1784209- 0.9784 60.31305 39.01045 185 1784461 1784461 MAX.chr21.44782441- chr21:44782441- 0.9688 16.58956 71.97633 186 44782498 44782498 MAX.chr22.23908718- chr22:23908718- 1 25.82947 20.84453 188 23908782 23908782 MAX.chr5.145725410- chr5:145725410- 0.9969 14.69927 29.27086 193 145725459 145725459 MAX.chr5.178957564- chr5:178957564- 0.9614 16.46627 42.22336 195 178957598 178957598 MAX.chr5.180101084- chr5:180101084- 1 23.37255 25.00699 196 180101094 180101094 MAX.chr5.42952185- chr5:42952185- 0.966 16.77837 67.63893 197 42952280 42952280 MAX.chr5.42994866- chr5:42994866- 0.9112 4.703287 161.8831 198 42994936 42994936 MAX.chr6.27064703- chr6:27064703- 0.9537 20.54983 23.77734 205 27064783 27064783 MAX.chr7.152622607- chr7:152622607- 0.9522 24.6674 20.98723 207 152622638 152622638 MAX.chr8.145104132- chr8:145104132- 0.9641 23.94389 106.2614 211 145104218 145104218 MAX.chr9.136474504- chr9:136474504- 0.951 20.88926 25.01507 215 136474527 136474527 MCF2L2 chr3:182896930- 0.9753 20.09711 22.94148 216 182897245 MSX2P1 chr17:56234436- 0.9105 20.25101 185.2593 222 56234516 NACAD chr7:45128502- 0.9583 24.13599 24.56509 223 45128717 NID2_B chr14:52535974- 0.966 21.89118 30.61013 225 52536161 NID2_C chr14:52536192- 0.9846 21.19688 35.70811 226 52536328 ODC1 chr2:10589075- 0.9896 5.239957 199.2568 231 10589243 OSR2_B chr8:99952801- 0.9599 24.39913 21.91589 235 99952919 PAQR6 chr1:156215470- 0.9965 1.875785 35.09138 238 156215739 PCDH8 chr13:53421299- 0.9907 14.32 28.05643 239 53421322 PIF1 chr15:65116285- 0.9537 43.87855 44.78209 244 65116597 PPARA chr22:46545328- 0.9896 1.934821 27.81555 248 46545457 PPP2R5C chr14:102247681- 0.9969 40.41616 21.95545 252 102247929 PRDM13_A chr6:100061616- 0.9537 24.24062 61.61066 253 100061742 PRHOXNB chr13:28552424- 1 32.97143 25.41024 255 28552562 PRKCB chr16:23847575- 0.9537 30.71429 443.1833 256 23847699 RBFOX3_A chr17:77179579- 0.9846 21.15348 20.09964 262 77179752 RBFOX3_B chr17:77179778- 0.9784 22.97297 38.87734 263 77180064 RFX8 chr2:102090934- 0.9475 14.08461 61.73279 264 102091130 SNCA chr4:90758071- 0.9622 14.42541 42.52051 283 90758118 STAC2_A chr17:37381217- 0.9815 43.97999 23.61791 286 37381303 STAC2_B chr17:37381689- 0.9938 59.47293 161.2592 287 37381795 STX16_B chr20:57225077- 0.989 1.467485 182.6884 289 57225227 SYT5 chr19:55690401- 0.9938 16.49149 33.17451 292 55690496 TIMP2 chr17:76921762- 0.9568 17.75848 42.58231 297 76921779 TMEFF2 chr2:193060012- 0.9753 17.97114 35.24222 299 193060126 TNFRSF10D chr8:23020896- 0.9475 22.13556 107.3874 301 23021114 TRH_B chr3:129694457- 1 18.95629 21.0275 304 129694501 TRIM67 chr1:231297047- 1 23.47643 15.57769 305 231297159 TRIM71_C chr3:32860020- 0.9826 28.31276 43.84559 308 32860090 USP44_A chr12:95942148- 0.9722 25.33383 22.23173 312 95942178 USP44_B chr12:95942519- 0.9688 29.71223 20.72773 313 95942558 UTF1 chr10:135044125- 0.9935 24.15274 23.83046 314 135044171 UTS2R chr17:80329497- 0.9896 37.98289 25.32411 315 80329534 VSTM2B_A chr19:30016283- 0.9654 57.09044 59.81456 319 30016357 VSTM2B_B chr19:30017789- 0.9673 32.07169 27.33698 320 30018165 ZFP64 chr20:50721057- 0.9506 27.53052 22.5886 322 50721235 ZNF132 chr19:58951402- 0.9804 39.76355 100.0992 323 58951775

TABLE 5 Table 5 shows 1) area under the curve for identified methylated regions distinguishing Luminal A breast cancer tissue from normal breast tissue, 2) the Fold Change (FC) for Luminal A breast cancer tissue vs. normal breast tissue, and 3) the Fold Change (FC) for Luminal A breast cancer tissue vs. buffy coat (normal). Region on Chromosome (starting base- Gene Annotation ending base) AUC FC Tissue FC Buffy DMR ARL5C chr17:37321515- 0.9083 10.00664 31.97539 13 37321626 BHLHE23_C chr20:61638088- 0.9184 31.17451 43.04012 23 61638565 BMP6 chr6:7727566- 0.9248 33.44248 32.18487 26 7727907 C10orf125 chr10:135171410- 0.9816 5.951195 52.52747 27 135171661 C17orf64 chr17:58499095- 0.9414 9.129866 128.5583 29 58499190 C19orf66 chr19:10197688- 0.9288 3.629997 23.26103 31 10197823 CAMKV chr3:49907259- 0.9265 31.61795 34.87738 38 49907298 CD1D chr1:158150864- 0.9575 26.85386 35.71281 47 158151129 CDH4_E chr20:59828479- 0.9575 19.38124 24.61343 53 59828729 CDH4_F chr20:59828778- 0.9167 27.70653 25.85724 54 59828814 CHST2_A chr3:142838025- 0.9167 47.12016 106.0335 56 142838494 CRHBP chr5:76249939- 0.9294 14.22073 22.1281 62 76249997 DLX6 chr7:96635255- 0.9622 13.78623 28.53928 67 96635475 DNM3_B chr1:171810648- 0.9087 29.14931 295.5986 70 171810702 DNM3_C chr1:171810806- 0.9753 23.67912 99.77376 71 171810920 DNM3_A chr1:171810393- 0.9134 21.31894 129.3404 69 171810575 ESYT3 chr3:138153979- 0.9479 39.19083 37.19512 78 138154071 ETS1_A chr11:128391809- 0.9089 40.45139 159.0444 79 128391908 ETS1_B chr11:128392062- 0.8872 34.63309 188.3098 80 128392309 FAM126A chr7:23053941- 0.9706 57.86891 65.82935 83 23054066 FAM189A1 chr15:29862130- 0.9757 18.04237 28.53505 88 29862169 FAM20A chr17:66597237- 0.9019 35.24514 24.36451 89 66597326 FAM59B chr2:26407713- 0.9479 1.945513 103.9384 90 26407972 FBN1 chr15:48937412- 0.9599 31.33933 27.92071 91 48937541 FLRT2 chr14:85998469- 0.9428 15.80425 20.40157 93 85998535 FMN2 chr1:240255171- 0.9294 27.79887 61.08723 94 240255253 FOXP4 chr6:41528816- 1 1.388687 +190DIV/0! 96 41528958 GAS7 chr17:10101325- 0.9282 39.97585 23.28643 99 10101397 GYPC_A chr2:127413505- 0.9379 16.91651 75.32742 108 127413678 GYPC_B chr2:127414096- 0.9727 15.16704 832.1792 109 127414189 HAND2 chr4:174450452- 0.9583 13.64474 20.65737 110 174450478 HES5 chr1:2461823- 0.9111 21.96548 15.9217 112 2461915 HMGA2 chr12:66219385- 0.9314 46.53533 21.43751 114 66219487 HNF1B_B chr17:36105390- 0.9926 2.464626 20.34797 116 36105448 IGF2BP3_B chr7:23513817- 0.969 15.15625 99.58003 124 2351411 IGF2BP3_A chr7:23508901- 0.9167 18.96654 90.76778 123 23509225 KCNH8 chr3:19189837- 0.9821 26.86423 11.12219 138 19189897 KCNK17_A chr6:39281195- 0.9111 64.74638 44.94467 139 39281282 KCNQ2 chr20:62103558- 0.9379 15.9322 58.35214 142 62103625 KLHDC7B chr22:50987219- 1 1.458785 126.5684 146 50987304 LOC100132891 chr8:72755897- 0.9477 21.07843 34.37075 153 72756295 MAX.chr1.46913931- chr1:46913931- 0.9074 23.06829 20.81013 164 46913950 46913950 MAX.chr11.68622869- chr11:68622869- 0.9395 46.67485 64.1812 169 68622968 68622968 MAX.chr12.4273906- chr12:4273906- 0.9379 20.87418 155.4373 170 4274012 4274012 MAX.chr12.59990591- chr12:59990591- 0.8807 14.01947 21.10553 171 59990895 59990895 MAX.chr17.73073682- chr17:73073682- 0.9449 1.052067 45.64784 174 73073814 73073814 MAX.chr20.1783841- chr20:1783841- 0.9074 27.09573 22.06724 184 1784054 1784054 MAX.chr21.47063802- chr21:47063802- 0.9757 16.51515 79.7561 187 47063851 47063851 MAX.chr4.8860002- chr4:8860002- 0.9363 16.17858 68.04479 192 8860038 8860038 MAX.chr5.172234248- chr5:172234248- 0.9201 1.531023 83.07827 194 172234494 172234494 MAX.chr5.178957564- chr5:178957564- 0.9392 11.40949 29.25659 195 178957598 178957598 MAX.chr6.130686865- chr6:130686865- 0.9583 39.03866 37.31522 202 130686985 130686985 MAX.chr8.687688- chr8:687688-687736 0.9286 24.48762 22.46817 212 687736 MAX.chr8.688863- chr8:688863-688924 0.9303 15.25862 30.30423 213 688924 MAX.chr9.114010- chr9:114010-114207 0.9085 25.1809 34.53142 214 114207 MPZ chr1:161275561- 0.933 36.3026 503.8832 221 161275996 NID2_A chr14:52535260- 0.9316 29.32631 35.83691 224 52535353 NKX2-6 chr8:23564115- 0.908 15.67986 32.03798 227 23564146 ODC1 chr2:10589075- 1 5.298588 201.4864 231 10589243 OSR2_A chr8:99952233- 0.951 17.65456 23.40924 234 99952366 POU4F1 chr13:79177505- 0.9241 14.6281 25.83187 247 79177532 PRDM13_B chr6:100061748- 0.9549 22.67697 52.7912 254 100061792 PRKCB chr16:23847575- 0.9248 26.98915 389.4325 256 23847699 RASGRF2 chr5:80256117- 0.9327 24.29321 45.671 261 80256162 RIPPLY2 chr6:84563228- 0.9216 20.4497 24 267 84563287 SLC30A10 chr1:220101458- 0.9346 21.20187 19.7307 279 220101634 ST8S1A4 chr5:100240059- 1 1.754394 257.6766 285 100240276 SYN2 chr3:12045894- 0.9232 22.95533 31.86263 290 12045967 TRIM71_A chr3:32858861- 0.9184 15.38071 50.65283 306 32858897 TRIM71_B chr3:32859445- 0.9375 15.41597 43.92036 307 32859559 TRIM71_C chr3:32860020- 0.9115 25.64374 39.71231 308 32860090 UBTF chr17:42287924- 1 2.648869 421.8795 310 42288018 ULBP1 chr6:150285563- 0.902 16.53425 26.75089 311 150285661 USP44_B chr12:95942519- 0.975 29.4964 20.57716 313 95942558 VSTM2B_A chr19:30016283- 0.9283 34.40535 36.04704 319 30016357

TABLE 6 Table 6 shows 1) area under the curve for identified methylated regions distinguishing Luminal B breast cancer tissue from normal breast tissue, 2) the Fold Change (FC) for Luminal B breast cancer tissue vs. normal breast tissue, and 3) the Fold Change (FC) for Luminal B breast cancer tissue vs. buffy coat (normal). Region on Chromosome (starting base- Gene Annotation ending base) AUC FC Tissue FC Buffy DMR ACCN1 chr17:31620207- 0.9198 23.85808 9.167347 4 31620314 AJAP1_A chr1:4715535- 0.9815 24.85037 23.66546 6 4715646 AJAP1_B chr1:4715931- 0.9491 33.32713 54.60366 7 4716021 BEST4 chr1:45251853- 0.9059 32.89966 62.95737 20 45252029 CALN1_B chr7:71801741- 0.9059 16.99878 31.42622 37 71801800 CBLN1_B chr16:49316198- 0.933 15.66904 39.58407 42 49316258 CDH4_E chr20:59828479- 0.9259 17.19561 21.83777 53 59828729 DLX4 chr17:48042562- 1 3.346919 60.11236 66 48042606 FOXP4 chr6:41528816- 1 1.056007 #DIV/0! 96 41528958 IGSF9B_B chr11:133825491- 0.9815 21.1913 21.56637 127 133825530 ITPRIPL1 chr2:96990968- 0.9074 21.92125 197.5706 134 96991328 KCNA1 chr12:5019401- 0.9414 53.02013 39.91732 136 5019633 KLF16 chr19:1857330- 0.8791 12.18471 92.18633 145 1857476 LMX1B_A chr9:129388175- 0.9965 2.639923 62.01749 149 129388223 MAST chr19:12978399- 0.9706 16.13892 22.56069 160 12978642 MAX.chr11.14926602- chr11:14926602- 1 3.646943 81.99557 168 14927148 14927148 MAX.chr17.73073682- chr17:73073682- 0.9514 1.236217 53.63787 174 73073814 73073814 MAX.chr18.76734362- chr18:76734362- 0.9414 15.62804 48.90311 177 76734476 76734476 MAX.chr19.30719261- chr19:30719261- 0.9101 23.15574 21.34761 178 30719354 30719354 MAX.chr22.42679578- chr22:42679578- 0.963 28.63358 21.76462 189 42679917 42679917 MAX.chr4.8860002- chr4:8860002- 0.9259 17.90907 75.323 192 8860038 8860038 MAX.chr5.145725410- chr5:145725410- 0.9012 10.81956 21.54514 193 145725459 145725459 MAX.chr5.178957564- chr5:178957564- 0.9028 14.08818 36.12539 195 178957598 178957598 MAX.chr5.77268672- chr5:77268672- 0.9228 16.4233 39.91228 199 77268725 77268725 MAX.chr8.124173128- chr8:124173128- 0.9105 12.93676 45.59879 209 124173268 124173268 MPZ chr1:161275561- 0.9653 19.98003 184.2234 221 161275996 PPARA chr22:46545328- 0.9931 1.592475 22.89388 248 46545457 PRMT1 chr19:50179501- 0.8837 11.53981 25.86275 257 50179635 RBFOX3_B chr17:77179778- 0.9012 18.327 31.01493 263 77180064 RYR2_A chr1:237205369- 0.9392 21.32044 25 268 237205428 SALL3 chr18:76739321- 0.96 58.85028 60.07958 270 76739404 SCRT2_A chr20:644533- 0.9871 19.11925 8.272966 272 644618 SPHK2 chr19:49127580- 0.9753 38.67547 42.87091 284 49127683 STX16_B chr20:57225077- 1 1.503476 187.169 289 57225227 SYNJ2 chr6:158402213- 1 1.81213 79.15141 291 158402536 TMEM176A chr7:150497411- 0.8719 18.02734 13.07736 300 150497535 TSHZ3 chr19:31839809- 0.9475 19.63569 29.13422 309 31840038 VIPR2 chr7:158937370- 0.9537 28.49829 22.56321 316 158937481

TABLE 7 Table 7 shows 1) area under the curve for identified methylated regions distinguishing BRCA1 breast cancer tissue from normal breast tissue, 2) the Fold Change (FC) for BRCA1 breast cancer tissue vs. normal breast tissue, and 3) the Fold Change (FC) for BRCA1 breast cancer tissue vs. buffy coat (normal). Region on Chromosome (starting base- DMR Gene Annotation ending base) AUC FC Tissue FC Buffy No. C10orf93 chr10: 134756078- 1 35.64082278 21.3938 28 134756167 C20orf195_A chr20: 62185293- 0.9537 25.6624628 88.34146 33 62185364 C20orf195_B chr20: 62185418- 0.9537 31.08894431 47.34177 34 62185546 CALN1_B chr7: 71801741- 1 22.4757876 41.55176 37 71801800 CBLN1_A chr16: 49315588- 1 23.38948327 22.60229 41 49315691 CBLN1_B chr16: 49316198- 0.9815 27.353707 71.4388 42 49316258 CCDC61 chr19: 46519467- 0.9667 48.80498092 67.25713 43 46519536 CCND2 chr12: 4378317- 0.9333 16.28123545 100.7685 44 4378375 CCND2 chr12: 4380560- 0.951 10.56487202 70.74468 45 4380681 CCND2 chr12: 4384096- 0.9907 25.60667341 76.22272 46 4384146 EMX1_B chr2: 73151663- 0.9833 13.75989446 30.57754 75 73151756 FAM150B chr2: 287868-287919 0.9306 32.67264761 21.96353 86 GRASP chr12: 52400919- 0.9259 28.3875581 48.04841 105 52401166 HBM chr16: 216426- 0.9706 35.04374159 35.09097 111 216451 ITPRIPL1 chr2: 96990968- 1 17.39816032 163.0944 134 96991328 KCNK17_A chr6: 39281195- 0.9583 36.55797101 25.37726 139 39281282 K1AA1949 chr6: 30646976- 0.9556 30.04064322 173.3102 143 30647084 LOC100131176 chr7: 151106986- 1 16.94187139 29.40354 152 151107060 MAST1 chr19: 12978399- 1 19.30541369 26.98715 160 12978642 MAX.chr1.8277285- chr1: 8277285- 0.9815 31.30790191 52.33035 165 8277316 8277316 MAX.chr1.8277479- chr1: 8277479- 1 18.61607143 45.48146 166 8277527 8277527 MAX.chr11.14926602- chr11: 14926602- 1 4.590639238 107.8495 168 14927148 14927148 MAX.chr15.96889013- chr15: 96889013- 0.9778 18.09917355 35.80772 173 96889128 96889128 MAX.chr18.5629721- chr18: 5629721- 0.9375 17.83216783 20.53691 177 5629791 5629791 MAX.chr19.30719261- chr19: 30719261- 1 33.50409836 30.88791 178 30719354 30719354 MAX.chr22.42679578- chr22: 42679578- 0.9778 37.74834437 39.34049 189 42679917 42679917 MAX.chr5.178957564- chr5: 178957564- 1 22.21108884 56.95444 195 178957598 178957598 MAX.chr5.77268672- chr5: 77268672- 0.9074 15.49630845 37.65949 199 77268725 77268725 MAX.chr6.157556793- chr6: 157556793- 0.9778 33.75787815 33.87352 203 157556856 157556856 MAX.chr8.124173030- chr8: 124173030- 1 23.47893058 63.5876 208 124173395 124173395 MN1 chr22: 28197962- 0.9352 23.36568394 26.69456 220 28198388 MPZ chr1 : 161275561- 0.8519 49.15590864 856.6978 221 161275996 NR2F6 chr19: 17346428- 1 13.02466029 353.7936 228 17346459 PDXK_A chr21: 45148429- 0.9722 75.55254849 229.9245 241 45148556 PDXK_B chr21: 45148575- 0.9778 24.6031746 68.40522 242 45148681 PTPRM chr18: 7568565- 1 27.52463054 20.36446 259 7568808 RYR2_B chr1: 237205619- 0.95 21.12877583 25.85603 269 237205640 SERPINB9_A chr6: 2902941- 0.9907 28.33433917 27.88833 274 2902998 SERPINB9_B chr6: 2903031- 0.9769 25.91687042 40.06479 275 2903143 SLC8A3 chr14: 70654596- 0.9706 16.90022757 46.84595 281 70654640 STX16_B chr20: 57225077- 1 1.678527607 208.9613 289 57225227 TEPP chr16: 58018790- 0.9222 14.38988095 44.1351 296 58018831 TOX chr8: 60030723- 0.9537 13.484375 86.64659 302 60030754 VIPR2 chr7: 158937370- 0.9074 30.22915651 23.9336 316 158937481 VSTM2B_A chr19: 30016283- 0.9853 42.3267861 44.34645 319 30016357 ZNF486 chr19: 20278004- 1 28.7755102 40.02498 324 20278145 ZNF626 chr19: 20844070- 1 72.64705882 47.34274 325 20844199 ZNF671 chr19: 58238810- 1 30.69748581 235.6787 326 58238955

TABLE 8 Table 8 shows 1) area under the curve for identified methylated regions distinguishing BRCA2 breast cancer tissue from normal breast tissue, 2) the Fold Change (FC) for BRCA2 breast cancer tissue vs. normal breast tissue, and 3) the Fold Change (FC) for BRCA2 breast cancer tissue vs. buffy coat (normal). Region on Chromosome (starting base- FC DMR Gene Annotation ending base) AUC Tissue FC Buffy No. ANTXR2 chr4: 80993475- 0.9074 28.18115 48.41438 12 80993634 B3GNT5 chr3: 182971589- 0.9136 118.1266 122.9242 16 182971825 BHLHE23_A chr20: 61637950- 0.9948 21.22272 21.07755 21 61637986 BMP4 chr14: 54421578- 0.9815 45.77028 21.74194 25 54421916 CHRNA7 chr15: 32322830- 1 349.4748 29.49189 55 32322897 EPHA4 chr2: 222436217- 0.9236 58.94207 21.52714 76 222436320 FAM171A1 chr10: 15412558- 0.9087 51.57005 26.28231 87 15412652 FAM20A chr17: 66597237- 0.996 30.89732 21.35891 89 66597326 FMNL2 chr2: 153192734- 0.9028 53.3376 24.66469 95 153192836 FSCN1 chr7: 5633506- 0.9028 25.15063 30.87569 97 5633615 GSTP1 chr11: 67350986- 0.9 >1 × 10⁶ >1 × 10⁶ 107 67351055 HBM chr16: 216426-216451 0.9 22.7961 22.82682 111 IGFBP5 chr2: 217559103- 0.9722 59.11994 22.99517 125 217559244 IL17REL chr22: 50453462- 1 28.30452 28.99172 129 50453555 ITGA9 chr3: 37493895- 0.9706 43.32188 35.86874 131 37493994 ITPRIPL1 chr2: 96990968- 0.9583 14.7331 147.0693 134 96991328 KIRREL2 chr19: 36347825- 0.9853 45.39026 35.4729 144 36347863 LRRC34 chr3: 169530006- 0.9306 22.69192 30.27401 156 169530139 MAX.chr1.239549742- chr1: 239549742- 0.916 20.67734 21.47568 163 239549886 239549886 MAX.chr1.8277479- chr1: 8277479- 0.8333 13.25255 32.37769 166 8277527 8277527 MAX.chr11.14926602- chr11: 14926602- 0.9922 3.97073 93.28576 168 14927148 14927148 MAX.chr15.96889013- chr15: 96889013- 0.9514 8.454545 16.72662 173 96889128 96889128 MAX.chr2.238864674- chr2: 238864674- 0.9762 27.89736 28.99259 181 238864735 238864735 MAX.chr5.81148300- chr5: 81148300- 0.9583 12.50391 24.59992 200 81148332 81148332 MAX.chr7.151145632- chr7: 151145632- 0.9444 8.972603 58.5148 206 151145743 151145743 MAX.chr8.124173030- chr8: 124173030- 0.9306 7.530176 56.77946 208 124173395 124173395 MAX.chr8.143533298- chr8: 143533298- 0.9097 32.741 20.5064 210 143533558 143533558 MERTK chr2: 112656676- 0.9222 27.51721 62.09376 217 112656744 MPZ chr1: 161275561- 0.9236 33.56504 584.9775 221 161275996 NID2_C chr14: 52536192- 0.9236 13.44693 22.6526 226 52536328 NTRK3 chr15: 88800287- 0.9167 20.89983 28.86352 229 88800414 OLIG3_A chr6: 137818896- 0.9198 15.98856 20.54162 232 137818917 OLIG3_B chr6: 137818978- 0.9012 11.04806 20.26448 233 137818988 OSR2_C chr8: 99960580- 0.9136 19.58805 32.89474 236 99960630 PROM1 chr4: 16084793- 0.9583 32.17623 41.64147 258 16085112 RGS17 chr6: 153452120- 0.9028 24.55645 20.63008 265 153452393 SBNO2 chr19: 1131795- 0.9012 58.01495 69.1242 271 1131992 STX16_B chr20: 57225077- 1 1.597137 198.8289 289 57225227 TBKBP1 chr17: 45772630- 0.9559 21.05769 41.61125 294 45772726 TLX1NB chr10: 102881178- 0.9074 22.34146 128.8689 298 102881198 VIPR2 chr7: 158937370- 0.9074 26.0117 20.59448 316 158937481 VN1R2 chr19: 53758121- 0.9583 17.79366 22.4549 317 53758147 VSNL1 chr2: 17720216- 0.9485 59.26645 43.69099 318 17720257 ZFP64 chr20: 50721057- 0.9167 25.93427 21.27889 322 50721235

TABLE 9 Table 9 shows 1) area under the curve for identified methylated regions distinguishing invasive breast cancer tissue from normal breast tissue, 2) the Fold Change (FC) for invasive breast cancer tissue vs. normal breast tissue, and 3) the Fold Change (FC) for invasive breast cancer tissue vs. buffy coat (normal). Region on Chromosome (starting base- DMR Gene ending base) AUC FC Tissue FC Buffy No. CDH4_E chr20: 59828479- 0.9319 24.19 24.91762 53 59828729 FLJ42875 chr1: 2987037- 0.9012 36.28 26.33723 92 2987116 GAD2 chr10: 26505066- 0.9016 25.3 33.18529 98 26505385 GRASP chr12: 52400919- 0.9311 40.47 56.12708 105 52401166 ITPRIPL1 chr2: 96990968- 0.91 32.57 236.8703 134 96991328 KCNA1 chr12: 5019401- 0.9147 55.3 35.34681 136 5019633 MAX.chr12.4273906- chr12: 4273906- 0.939 25.47 153.0038 170 4274012 4274012 MAX.chr18.76734362- chr18: 76734362- 0.9304 21.29 55.1493 177 76734476 76734476 MAX.chr19.30719261- chr19: 30719261- 0.9174 28.37 22.54408 178 30719354 30719354 MAX.chr4.8859602- chr4: 8859602- 0.9211 11.78 24.06671 191 8859669 8859669 MAX.chr4.8860002- chr4: 8860002- 0.9401 24.35 83.41947 192 8860038 8860038 MAX.chr5.145725410- chr5: 145725410- 0.9266 14.46 23.92735 193 145725459 145725459 MAX.chr5.178957564- chr5: 178957564- 0.9022 17.01 35.18328 195 178957598 178957598 MAX.chr5.77268672- chr5: 77268672- 0.9044 16.79 34.23046 199 77268725 77268725 MPZ chr1: 161275561- 0.9007 56.97 527.027 221 161275996 NKX2-6 chr8: 23564115- 0.9056 19.22 32.40724 227 23564146 PRKCB chr16: 23847575- 0.9032 35.63 371.6895 256 23847699 RBFOX3_B chr17: 77179778- 0.9241 22.81 32.30013 263 77180064 SALL3 chr18: 76739321- 0.9136 66.21 56.29973 270 76739404 VSTM2B_A chr19: 30016283- 0.9278 43.07 37.76572 319 30016357

Next, SYBR Green Methylation-specific PCR (qMSP) was performed on the discovery samples to confirm the accuracy and reproducibility of the candidate DMR's shown in Table 2. In addition, a 16 marker subset was run on frozen low grade and high grade DCIS samples to test applicability (22 high grade/CIS/P3 DCIS (ductal carcinoma in situ); 11 low grade/P1 DCIS).

qMSP primers were designed for each of the marker regions using Methprimer software (Li L C and Dahiya R. Bioinformatics. 2002 November; 18(11):1427-31) They were synthesized by IDT (Integrated DNA Technologies). Assays were tested and optimized (using the Roche LightCycler 480) on dilutions of bisulfite converted universally methylated DNA, along with converted unmethylated DNA and converted and unconverted leukocyte DNA negative controls (10 ng/ea). Assays taken forward needed to demonstrate linear regression curves and negative control values less than 5-fold below the lowest standard (1.6 genomic copies). Some of the more promising DMRs which had assay or control failures were re-designed. Of the 127 total designs (Table 10 shows the forward and reverse primer sequence information for the 127 total designs), 80 high performing MSP assays met QC criteria and were applied to the samples. The MSP primer sequences, each of which include 2-8 CpGs, were designed to provide a quick means of assessing methylation in the samples, and as such, were biased for amplification efficiency over trying to target the most discriminate CpGs—which would have required lengthy optimization timeframes.

DNA was purified as described in the discovery RRBS section and quantified using picogreen absorbance (Tecan/Invitrogen). 2 ug of sample DNA was then treated with sodium bisulfite and purified using the Zymo EZ-96 Methylation kit (Zymo Research). Eluted material was amplified on Roche 480 LightCyclers using 384-well blocks. Each plate was able to accommodate 2 markers (and standards and controls) for a total of 40 plates. The 80 MSP assays had differing optimal amplification profiles (Tm=60, 65, or 70° C.) and were grouped accordingly. The 20 uL reactions were run using LightCycler 480 SYBR I Master mix (Roche) and 0.5 umoles of primer for 50 cycles and analyzed, generally, by the Fit Point 18% absolute quantification method. All parameters (noise band, threshold, etc.) were pre-specified in an automated macro to avoid user subjectivity. The raw data, expressed in genomic copy number, was normalized to the amount of input DNA (0-actin). Results were analyzed logistically using JMP and displayed as AUC values. Twelve comparisons were run: each breast cancer subtype vs normal breast, and each subtype vs buffy coat. In addition, the methylation fold change ratio (mFCR) was calculated for each comparison using both average and median fractional methylation (FCR=cancer(methylated copies/β-actin copies)/normal(methylated copies/β-actin copies)). Both of these performance metrics were critical for assessing the potential of a marker in a clinical blood-based test.

>90% of the markers tested yielded superior performance in both AUC and FCR categories, with numerous AUCs in excess of 0.90, cancer vs normal tissue FCRs>10, and cancer vs buffy coat FCRs>50.

Table 11 shows area under the curve for the identified 80 methylated regions distinguishing basal/triple negative breast tissue, HER2+ breast tissue, Luminal A breast tissue, Luminal B breast tissue, BRCA1 breast tissue, and BRCA2 breast tissue in comparison with normal breast tissue.

Table 12 shows area under the curve for the identified 80 methylated regions distinguishing basal/triple negative breast tissue, HER2+ breast tissue, Luminal A breast tissue, Luminal B breast tissue, BRCA1 breast tissue, and BRCA2 breast tissue in comparison with normal buffy coat.

Table 13 shows methylation fold change for the identified 80 methylated regions distinguishing basal/triple negative breast tissue, HER2+ breast tissue, Luminal A breast tissue, Luminal B breast tissue, BRCA1 breast tissue, and BRCA2 breast tissue in comparison with normal breast tissue.

Table 14 shows methylation fold change for the identified 80 methylated regions distinguishing basal/triple negative breast tissue, HER2+ breast tissue, Luminal A breast tissue, Luminal B breast tissue, BRCA1 breast tissue, and BRCA2 breast tissue in comparison with normal buffy coat.

In the DCIS high grade vs low grade comparison, AUCs of the 16 markers tested ranged from 0.57 to 0.92. Several combinations of two markers achieved 95% sensitivity at 91% specificity (only 1 false positive) (Table 15). A 3 marker combination (SCRT2_B, ITPRIPL1, MAX.chr8.124173030-124173395) was 100% sensitive at 91% specificity.

TABLE 10  SEQ SEQ Gene  DMR Forward Primer ID Reverse Primer ID Annotation No. 5′-3′ NO: 5′-3′ NO: AADAT-RS 2 GAG TTT CGG CGG 1 CGC TAC GTC TAA 2 CGT TTT TCG CTT CCC GCG C ABLIM1-FS 3 TTT TCG ACG AGT 3 GCG AAT CTA TCT 4 AGG ATT GAA GAA ACC GAA ACG CGC GGA AC T AJAP1_A 6 TTT TGA TTT GTA 5 GTA TAA ACG CGT 6 ATA TAG AGG AAA AAA TAC CAA ACT GCG TCG T AAA CGA A AJAP1_B 7 GTT TCG AGA AAG 7 ACT CCC AAC GAA 8 GAG AAG GGG GAG AAC TTC GCA AAC C G ALOX5-RS 9 GTT TTT TGT CGG 9 CCA AAA ATT AAA 10 GAG TTA TTC GT TTA AAA ACG CTA CGC A ASCL2-RS 14 GTT TTA GGA GGG 11 AAC ACG ACT ATT 12 TGG GGC GT CGA AAA ACG CGC A ATP6V1B1-RS 15 TTC GTA GTA TCG 13 GAA ATA ATA AAA 14 GGA GTC GA ACG CCG CAC GCT BANK1-FS 17 GTC GTA GTT TTC 15 CGA ACG CTA CCT 16 GCG GGT GGT AAG AAA CTC TCC CGA C C BEST4-RS 20 GGA ATC GCG AGT 17 AAA TAC AAT TAC 18 TTT GGG ATA GTC G ACC CTC TAC CGC C BHLHE23_C 23 GAG GCG TTC GGT 19 CCC CGA CCT ATA 20 GGG ATT TC AAC CTA CGA CGC T BHLHE23_D 24 GAG GAG GTA GCG 21 CGC GTC GAT CTA 22 GGC GTC GA ACT TAC CTA CGA A C10orf125-FS 27 TTG CGT TTA TCG 23 GCA CTA CTA TCC 24 ATT TCG TTT TCG T CCC GAA CTA CTC TAC GC C17orf64-RS 29 TTA TTA GGC GGG 25 CTC GAA TCC CTA 26 GAG TCG GGT GTC AAA AAC TCG CGA A C19orf66-FS 31 AGG AAA TTC GGT 27 AAA CCC CTA CAA 28 AGC GAT TAT ACG G CCT CAC CGT ACA CGA T CALN1_A 36 CGG AGT TAA TAG 29 CAA ACC CCC GAA 30 GTA CGG GAG GCG CTA TCG CGA A T CAPN2-FS 39 CGG GTA TCG CGG 31 TAT CGT AAA AAC 32 TTA AGT TGG C CCA ACC CCT CGA C CD1D-FS 47 GGG ATT GGT GAG 33 CTC CCC GAA ACC 34 ATT CGG GAC GT AAA AAA CAA CGA A CDH4_E 53 GTT TTA AAT CGT 35 ACG AAC GAA AAC 36 ATT CGT AGT TCG TTT CCT AAA CGA G A CHST2_A 56 GCG TTT TTT TAT 37 ACC GAC ACT ACC 38 CGT TTT AGG GCG AAC CTC TCC GAA T CHST2_B 57 TGC GGG GAT TTT 39 CCG ACG AAC TAT 40 TAG CGG AAG C CCG ACT ATC ACT CGT T CLIC6-FS 58 GTA GTA GGT GGA 41 CTC TCG AAA ACC 42 GGG GGC GAG TTC GCA AAA TCC TCG CLIP4-FS 59 GGT AAT ATT GCG 43 AAC AAT CAA ATA 44 ATA TTT CGT AGA ATC GAA CGC ACG CGT C COL23A1-RS 60 GTC GTT TTT CGT 45 AAA ACT AAA TAA 46 TAC GAA GCG GC ATC TAT CCT CGA T CXCL12-FS 63 GCG TCG GCG GTT 47 AAC GAA TCT CAT 48 TTT AGT AAA AGC TAA ATC TCC CGT C DBNDD1R-FS 64 GAT TTT CGG GAG 49 CTT CCC CGC AAC 50 CGG CGA GAA CCG DLX4-FS 66 TTC GTT GGT ATA 51 CGA ATA CCG AAA 52 TTC GCG TAG GTG TCT ATA ACC CCG C AA DLX6-FS 67 ATT ATG ATT ACG 53 CTC CAT AAA AAC 54 ATG GTT GAC GG GAA TTT AAA CGA A DNM3_A 69 TTT GGT TAT AGA 55 ATC GAA CCA CCA 56 ACG TAG AGG TCG AAC CAA ACG C T DSCR6-FS 72 GGG AAG TTT AGT 57 ACT AAA AAC GTT 58 AGG TGA GCG T TCC GTC GAA CGC A DTX1-RS 73 GTT GGT AGG AGT 59 ATC GCA ATC GTA 60 AGG GTT GGT TCG ACC CGT AAA CGC A EMX1_A 74 ATT CGT ACG GTT 61 GAC CAA CTA CTT 62 TTT TCG TTT TCG  CCG CTC GAC GC T ETS1_B 80 CGG ATT TAG CGG 63 TTT AAA ACG TTT 64 TCG AGA CG CTC GCG ACG CC FAM126A-FS 83 TCG TTA GGC GAT 65 TAA AAA AAC CAT 66 GAT AAT TAG CGA AAA CCC TAA CGA C FAM129C-FS 34 GTT GGA GAA GAC 67 CCA AAA CCT CAC 68 GAT TCG TTC GGA TCC TCA ACC GC C FBN1-FS 91 CGC GAT GCG CGT 69 GAC GCG ACT AAC 70 TTT GAA C TTC CAA CCT AAC GAA FMN2-RS 94 TTT TCG TGG TTG 71 GCC GCG CTC TAC 72 TCG TCG TTG C ACT AAA CAT ATT CGC FOXP4-FS 96 CGG GGA AGT GGG 73 AAA AAA ACT AAA 74 AGT TTT TAG CG TCA AAA CCG CGA C GAS7-FS 99 GCG AGT TCG CGT 75 ACC GAC GCTACC 76 TGT TTA CGT TTC TAT AAC TCC ACG CT GP5-RS 104 TTA GGT TTG TTT 77 TCT ACA AAA CGC 78 ATT AAT TTT ACG T CGC GAC GRM7-FS 106 GTT AAT TCG AGA 79 GAC CAA AAA AAA 80 GCG CGA GGC GT TAA AAA ATC CCG CGA C GYPC_B 109 TAA AGA AAT AGA 81 CGA ACT AAA AAA 82 AAG CGG GCG ATA ACC GCC AAC CCG CGT HHEX-RS 113 GGG TTT TGC GGT 83 AAT AAC AAA CGC 84 TAA TGG CG GTC CCG AAA ACG A HNF1B_B 116 TTA GTT TTT TTT 85 AAC TTT TCC ACC 86 GGT TTT TAT TTG GAT TCT CAA TTC AAT TTC GA CG HOXA1_A 117 ATT TAA ATT TTC 87 ACA CTC CAA ATC 88 GGC GTT TCG TCG GAC CTT TAC AAT T CGC HOXA7_A 119 AGT TTG GTT CGT 89 AAC GCG ACT AAA 90 TTA GCG ATT GCG  ACC AAT TTC CGC T A IGF2BP3_A 123 TTT ATT TGT TTT 91 AAA TAT ATA CCC 92 TAT CGT TCG TCG G GAT TTC CCC GTT IGF2BP3_B 124 TAA TCG GCG TCG 93 CCG TCA ACC AAT 94 AGA GAG ATA TCG T CGA AAA CGA A IL15RA-FS 128 TCG TTT ATT TCG 95 AAC CAA CCT AAA 96 TTT TTT TTG TCG A ATC TAC ACT CGC A ITPRIPL1-FS 134 GGG TCG TAG GGG 97 CAT ACT TAT CCG 98 TTT ATC GC AAC GTC TAA ACG TC ITPRIPL1-FS 134 GGT TTT AGC GAT 99 CAC GAT CTT AAA 100 GAA TCG GAC GT AAA ACA ACG CGA C KCNH8-RS 138 CGT ATT TTT AGG 101 ACA CTA TTA CCC 102 TTT AGT TCG GCG GCG AAA AAA CGA T T KCNK17_B 140 GAG TTT GTT TGG 103 CCA AAT ATA ACG 104 GGG TTG GTC GTA TTT AAC TCT TTA TTC CCA CGA A KCNK9-FS 141 TTT TTT TTG ATT 105 CTA ATA AAC GCC 106 CGG ATT TTT TCG  GCC GTA TTC GAC G G KLF16-FS 145 TTT TCG CGT TGT 107 TAC ACA ACC ACC 108 TTT TAT TTA TCG CAA CTA CTC CGC T G KLHCC7B-RS 146 TGT TGT TGG GTA 109 CGA AAA CCC AAC 110 AAG GTT AGT ACG TCC CGA A T LAYN-RS 147 TTT TTG CGG TCG 111 CTT ACC AAC TAA 112 TTT TTC GGA GC CCC CCG CCT ACC G LIME1-RS 148 CGT TTT AGT AGG 113 CCC GAA AAC CAA 114 GAT TGG GGG CGA AAT AAA ATC CGC A LMX1B_A 149 CGG AAT AGC GCG 115 TTT AAC CGT AAC 116 GTC GTT TTT TC GCT CGC CTC GAC LOC100132891-FS 153 GTC GGT TGT GTT 117 AAA AAA AAC CCC 118 TAG AGC GTA GCG GAC GAC GAA T LOC100132891-FS 153 GTT GCG ATT GTT 119 ATA ATA ACA AAA 120 TGT ATT TTG CGG AAC CCC TCC CGA C LSS-FS 157 AGT TTC GTT AGG 121 CAA CTA AAA CTC 122 GAA GGG TTG CGT TAC CGC GCT CGA C T MAGI2-RS 159 AGG AAG GGT TTC 123 AAA AAA ATC AAC 124 GAG TTT AGT GCG GCG TCC TCC TCG G C MAST1-RS 160 TTT CGA TTT CGT 125 AAA CTA AAC GAC 126 TTT TAA ATT TCG  CTA ACC CTA CGT T A MAX.chr1. 166 AAG TTT ACG CGC 127 CGA AAC GAC TTC 128 8277479- GAG TTT GAT CGT TCT CCC CGC A 8277527-RS C MAX.chr11. 168 TTT AGT TCG CGG 129 GAA AAC ACA ATA 130 14926602- AAG TTA GGT TCG  AAC CCC GCC GTC 14927148-FS G MAX.chr11. 169 GTT AGA TTG TAG 131 AAA AAA CGA CTA 132 68622869- GAG GGA TTA GCG AAA AAT TCA CGC 68622968-FS G C MAX.chr12. 170 TTT GGA GTT TGG 133 CGA CGA AAC TAA 134 4273906- GGG ATC GAT AGT AAC CGC GTA CGT 4274012-FS C A MAX.chr12. 170 TTT GGA GTT TGG 135 CGA CGA AAC TAA 136 4273906- GGG ATC GAT AGT AAC CGC GTA CGT 4274012-FS C A MAX.chr12. 171 ATT ATA TTG GGG 137 AAC AAA CAA TTC 138 59990671- GCG TTA GGT TCG GCA CGT AAA CGA 59990859-FS G A MAX.chr15. 173 GGG CGG TTT ACG 139 GCG TCT CGA ACC 140 96889013- TGG ATT TTT ATA GTA CCC TAA CGT 96889128-FS GAT TTT C A MAX.chr17. 174 CGT CGT TGT TGA 141 CGC TTC CTA ACA 142 73073682- TTA TGA TCG CGG ACC TTC CTC GAA 73073814-RS MAX.chr18. 177 TTA ACG GTA TTT 143 AAA AAA AAC TCG 144 76734362- TTT GTT TTT TCG TCC CCG CGC T 76734476-RS T MAX.chr19. 179 TCG GTT AGT TCG 145 TAT TAA CCG AAA 146 46379903- AGG TAG GAA GTT AAC GAA AAC CAA 46380197-FS TTG C ATC CGA MAX.chr19. 179 AGT TTT GTT GTT 147 AAA AAC TAA AAA 148 46379903- TTG GGT AGG TCG CCT TTC TCT CGA 46380197-FS G C MAX.chr2. 180 GCG TTG AGA GTG 149 ACT ACC TAA ACT 150 223183057- ACG GAT ATT TTT CCG AAC ACG CCC 223183114-RS CGT C G MAX.chr20. 185 TTA GCG TAT CGG 151 GAA AAC GAA AAA 152 1784209- GAA TTA GGG GGA ACG ACG CGC A 1784461-FS C MAX.chr20. 185 TCG TTT TTT AGG 153 GAA CCG TAT TTA 154 1784209- TGG GGA AGA AGC AAA CCA ATC CCC 1784461-RS G GC MAX.chr4. 191 AAT TGG GGT TCG 155 TTA CCC CTA CCC 156 8859602- GGG TTC GGT AC AAA AAA ATA CGC 8859669-RS T MAX.chr5. 193 GGG GTT AGA GTT 157 CGC GTC TCC CGT 158 145725410- TCG CGT TCG C CCT ATC TAT ATA 145725459-RS CGT C MAX.chr5. 198 TAG GAA TTT TTT 159 CAC AAA AAC TCG 160 42994866- AAA TTC GTT TTA ATA CAA TTA CCG 42994936-FS CGG TT MAX.chr5. 199 TAT TTT ATA GTC 161 GTC GAT AAA AAA 162 77268672- GCG TTA AAA GCG  CCT ACG CGA CGA 77268725- T A FS MAX.chr6. 204 GAT TTA GTT TTT 163 TAT TAA AAA CGA 164 157557371- CGG GTT TAT AGC CCA AAC CTC CGC 157557657- GG A FS MAX.chr8. 208 TGG TTG TAG GCG 165 AAA AAC GAC CCT 166 124173030- TTT TGT TGG AGT AAC CAC CCT CGT 124173395- TC T FS MCF2L2-FS 216 TTT TGC GTA GTT 167 CCC GCA TTC CCG 168 GGG TAG GGT TCG AAA AAA ACG AT G MCF2L2-RS 216 TTA GGG TTT TTT 169 ATC CCC CGT ACG 170 TCG AGG AGT TCG AAA CTA AAC GCG A MCF2L2-RS 216 GCG TTC GTA TTT 171 TCT ACG TAA CTA 172 TCG GGA GAG GC AAC AAA ACC CGA A MIB2-FS 219 CGT TTT GTG TTT 173 AAA ACC CCA AAA 174 TAT AAA AAG AAA ACG CCC GAT GAT TTT CGG MPZ-FS 221 GGG GCG TAT ATA 175 AAA AAA AAC CCT 176 TTA GTT ATC GAG AAA AAC CGC CGA CGA A MSX2P1-FS 222 TTC GTT TAA TGA 177 TAA AAC AAA CTA 178 GAA GGG GTT AGC AAA ACC TTA ACG GG CGA CGC T NACAD-RS 223 GGG GAG GGA GTT 179 GTA CGC GAA CTC 180 TTT TTT AC GCC AAA CAC TAC G ODC1-FS 231 GTA GGG TTG GTA 181 AAC CCA TCT AAT 182 GTC GTT TTT ACG  TAC AAA ATA CCT T CGA T ODC1-RS 231 GGT TTT ATA GGG 183 AAA ACC TCG TCT 184 GAA ATT ATT TTC TTA TAA CAT CGA GT A ODC1-RS 231 TAG GAT ATT TCG 185 AAC AAA ACT AAC 186 ATG TTA TAA AGA AAC CGC CTC CAC CGA G OSR2_A 234 TTT GGA GTT ATC 187 GCA CGC CGA AAA 188 GGA AGG CGA AAG AAT AAA AAC GAA TAC OTX1-RS 237 TTT TCG ATA TCG 189 ATA ACT TAA AAC 190 ATA TCG AAG GCG CCT AAA TTC CGC T C PAQR6-FS 238 GCG GGT AGT AGG 191 CCG ACT TCC GTA 192 AAG ATT AGT AGC CGA AAC CGT A GG PLXNC1_A 245 TAA TAG AGG TTT 193 AAC GCA CCC TAA 194 GCG TTG GAA TCG ACA AAA CCA CGA A C PLXNC1_B 246 TGA AGA GTT GTT 195 GCC AAA AAT TCG 196 AGT TCG TTT AGC ATT CCA ACG CA GT PPARA-FS 248 TAG TGG TAG GTA 197 ATC AAA ACT CCC 198 TAG TTG GTA GCG CTC CTC GAA AAC G G PPARG-RS 249 GTT TTT AAG CGG 199 AAA AAA AAT CCC 200 CGG TCG T GTT CGC T PRKCB-RS 256 GCG CGC GTT TAT 201 AAA ATC AAA AAC 202 TAG ATG AAG TCG CAC AAA TTC ACC GCC PRMT1-FS 257 CGG GGA GAG GAG 203 CAA CTT AAA CAC 204 GGG TAG GAT TTA CAC TTC CTC CGA C A RBF0X3_A 262 TGT TTT TTT TGT 205 AAA TAA CTA ACT 206 TCG GGC GG CCT ACT CTC GCC CGC T RFX8-FS 264 ATA GTT TTT TAA 207 AAA AAC AAC TCC 208 TTT TCG CGT TTC AAC CCA CAC CGC GTC GA RIC3-RS 266 GCG GGA GGA GTA 209 AAA AAC AAA ATA 210 GGT TAA TTT TCG A CGC GAA ACG CAC G SCRT2_B 273 CGA GAA GGT TTT 211 TAC GTA TCC ATA 212 GTC GTA GAC GTC CCC GCG CTC G GT SLC16A3-FS 276 TTT GTT TGT ATA 213 CGC CTA ACT ACC 214 ATA GGG GTT GCG GAA AAA TAC CGA G A SLC22A20-FS 277 GGT GGG GTT ATT 215 CGA ACC AAA CCT 216 TTT TTA TGG AGT ACG ATT CCC GAA CGA TTC SLC2A2-RS 278 GGG AGA AGA GAA 217 TCT TAT ACT CAA 218 TGG TTT TTT GTC CCC CGA CCT ACC GTC GAC SLC30A10-FS 279 GTT TTA TTC GGG 219 AAA AAA CCG CGT 220 GTT TTA GCG TTA TAC TCA ACG CGC TTT ACG G SLC7A4-RS 280 GTT TAG AGC GGA 221 CGC CTA TTC TTA 222 GGT AGC GGT TGC AAC CTA AAC CCG TC SLITRK5-FS 282 CGT AGA GGA TTA 223 TAC TAT AAC TAC 224 TAA AGA TTT GTA TAC GAT AAC GAC CGA GAC GAC SPHK2-RS 284 AGA TTT CGG TTT 225 ATT AAT ACT AAC 226 TTG TTT CGA TTT TTA CGA AAC CGC TCG T C ST8SIA4-RS 285 ATT ATT TTT GAG 227 AAA TTT CTC TCC 228 CGT GAA AAA TCG AAT TAA ATT CCG T TA STAC2_B 287 GTG GGT TTG TCG 229 AAA TAA CCG CGT 230 TCG GAT TTC G CAT CCG ATT CGT T STX16_A 288 TGG ATG TTT TAT 231 GTA CTT TTT CTC 232 ATT AAT TTT TAG TCA CGA AAA ATA TTG TAT AAC G TTC CCG C STX16_B 289 TGC GTG GAA TAA 233 GCT CAA CAC ACG 234 ATT TTA TAT ACG AAA AAC CCT CGA T A STX16_B 289 CGG TGC GGG GTT 235 TCC ACG CAA AAA 236 TTA ATA AAG GAT CAA AAA ACG CGT C A SYNJ2-FS 291 GGC GTA GTT ATG 237 ATC CTT TCG ACC 238 ATT TCG TTT TTT CTA CGT ACC TCG CGT AT TBX1-FS 295 TTT ACG ATT ATT 239 GAA CCC GAC GAA 240 GTT TTA GAT AAT CTT CGA A ACG G TMEM176A-FS 300 GGG AAA TCG CGT 241 AAA ACG ACG AAA 242 AGT TTG GGC AAA CGA AAA CGA C TNFRSF10D-FS 301 AGT TAT CGC GAT 243 AAA CGA TTA CCT 244 CGG TTT GGG TTA CTT TCG TTC GTT AC CGT T TRH_A 303 CGG CGG TTT ATT 245 CGA CAA ATC AAA 246 TGA AGA GGG TTC AAT CTA CAA CGC T TRIM67-RS 305 TTT TAA CGT TAG 247 CGA ACA AAC CAA 248 TTA CGA GTT GCG ACA ACC GAA G UBTF-RS 310 GTA GAT TAG GCG 249 GAA CAA AAA CAT 250 GGG GCG A AAA CTA ATA CAA ATA TCT CCC G ZSCAN12-FS 327 GGA GGG AGA GTT 251 CTA AAC CCC TCA 252 TTT CGC GGA TTC AAC CCT AAC CGA T GRASP 105 TGT TTT CGG ATA 253 ACG AAC GAA CTA 254 CGG CGA GC TAC GCG ACG CT

TABLE 11 Table 11 shows area under the curve for the identified 80 methylated regions distinguishing basal/triple negative breast tissue, HER2+ breast tissue, Luminal A breast tissue, Luminal B breast tissue, BRCA1 breast tissue, and BRCA2 breast tissue in comparison with normal breast tissue. Basal- like/ Triple DMR Gene Annotation Negative HER2+ Luminal A Luminal B BRCA1 BRCA2 No. BHLHE23_C 0.75 0.93567 0.80392 0.74728 0.82716 0.70782 23 CALN1_A 0.89699 0.86842 0.73638 0.98039 0.95679 0.68724 36 CD1D 0.66204 0.82066 0.91503 0.78431 0.83951 0.66667 47 CHST2_A 0.65972 0.8655 0.94118 0.66231 0.69753 0.63374 56 FAM126A 0.36806 0.64717 0.86928 0.53377 0.59877 0.72428 83 FMN2 0.55324 0.93762 0.8976 0.7037 0.75926 0.65432 94 HOXA1_A 0.60417 0.94152 0.81264 0.57734 0.56173 0.58848 117 HOXA7_A 0.52315 0.95906 0.84423 0.76144 0.82716 0.73251 119 KCNH8 0.5463 0.96881 0.85839 0.72985 0.73457 0.78189 138 LOC100132891 0.81019 0.9883 0.94771 0.80174 0.8642 0.75309 153 MAX.chr1.8277479-8277527 0.68981 0.66569 0.73203 0.69172 0.99383 0.607 166 MAX.chr15.96889013-96889128 0.68287 0.93372 0.82353 0.88235 0.98765 0.80247 173 NACAD 0.86111 0.8577 0.7146 0.70806 0.84568 0.7284 223 SLC30A10 0.64352 0.77388 0.94989 0.57516 0.58333 0.77366 279 TRIM67 0.81134 0.97856 0.88126 0.77015 0.73457 0.71811 305 ATP6V1B1 0.8912 0.8616 0.83007 0.82789 1 0.81893 15 BANK1 0.75231 0.70175 0.83878 0.66231 0.91975 0.79835 17 C10orf125 0.39352 0.76706 0.94444 0.70806 0.73765 0.7037 27 C17orf64 0.58333 0.97856 0.85185 0.81699 0.81173 0.86831 29 CHST2_B 0.59722 0.91228 0.89325 0.68192 0.64506 0.69547 57 DLX4 0.86574 0.85965 0.61547 0.83333 0.84877 0.79424 66 DNM3_A 0.35185 0.92203 0.92375 0.58388 0.62346 0.65021 69 EMX1_A 0.74537 0.91813 0.86275 0.68627 0.94444 0.67901 74 FOXP4 0.7037 0.61209 0.64488 0.58388 0.91358 0.53086 96 GP5 0.87731 0.77388 0.82353 0.72113 1 0.65844 104 IGF2BP3_A 0.64583 0.92008 0.87364 0.75599 0.69753 0.74897 123 ITPRIPL1 0.94676 1 0.91285 0.94336 1 0.95473 134 KLHDC7B 0.63194 0.5614 0.58606 0.66449 0.42593 0.55144 146 LMX1B_A 0.77083 0.81871 0.878 0.76253 0.80864 0.79012 149 MAX.chr11.14926602-14927148 0.98611 0.93567 0.94553 0.94553 1 0.98354 168 MAX.chr5.42994866-42994936 0.84259 0.91618 0.90196 0.93682 0.93827 0.95885 198 MAX.chr8.124173030-124173395 0.87963 0.8577 0.87146 0.89542 0.96914 0.77778 208 MPZ 0.9294 0.98246 0.93682 0.88344 0.86111 0.79835 221 ODC1 0.3588 0.89474 0.83442 0.60349 0.46914 0.55967 231 PLXNC1_A 0.61806 0.83626 0.8976 0.57952 0.67901 0.65844 245 PRKCB 0.91204 0.96491 0.99782 0.97603 0.88272 0.78189 256 ST8SIA4 0.84722 0.47173 0.80392 0.66885 0.57407 0.56379 285 STX16_B 0.84259 0.7115 0.80174 0.71895 0.98765 0.59259 289 UBTF 0.69676 0.67836 0.91939 0.68192 0.83333 0.76132 310 LOC100132891 0.66898 0.94542 0.93682 0.79303 0.96914 0.83951 153 ITPRIPL1 0.88657 0.98051 0.90741 0.87364 0.99383 0.86008 134 ABLIM1 0.7662 0.91618 0.79303 0.67756 0.83951 0.83128 3 KLF16 0.91898 0.75049 0.64924 0.9085 0.76543 0.66255 145 MAX.chr12.4273906-4274012 0.83796 0.88499 0.86928 0.94336 0.72222 0.74074 170 MAX.chr12.59990671-59990859 0.68056 0.89084 0.77342 0.53595 0.54938 0.60494 171 MAX.chr19.46379903-46380197 0.72801 0.96296 0.79085 0.83987 0.91975 0.82099 179 ZSCAN12 0.76852 0.88694 0.74946 0.78214 0.82099 0.70782 327 AADAT 0.49537 0.7193 0.58606 0.56427 0.69136 0.61317 2 BHLHE23_D 0.65972 0.85185 0.86492 0.84314 0.85802 0.70782 24 COL23A1 0.66898 0.89669 0.82353 0.68954 0.49074 0.92181 60 CXCL12 0.56019 0.70565 0.66231 0.59695 0.85802 0.72428 63 KCNK9 0.80556 0.88499 0.82789 0.67756 0.84568 0.70782 141 LAYN 0.55787 0.96686 0.76471 0.63834 0.62963 0.84774 147 OTX1 0.60648 0.78363 0.84749 0.69717 0.98765 0.81481 237 PLXNC1_A 0.70718 0.85673 0.91068 0.62854 0.67284 0.68519 245 RIC3 0.78009 0.90643 0.74292 0.7756 0.83951 0.69136 266 SCRT2_B 0.91319 0.95517 0.73638 0.7658 0.91975 0.47119 273 IGF2BP3_B 0.62037 0.96296 0.87582 0.66885 0.73457 0.7572 124 MAX.chr17.73073682-73073814 0.78009 0.67836 0.59913 0.52505 0.88889 0.73251 174 TBX1 0.45139 0.49708 0.75163 0.69499 0.48765 0.46914 295 ALOX5 0.44676 0.91618 0.76688 0.60784 0.47531 0.74486 9 ASCL2 0.82899 0.92271 0.77101 0.48913 0.82609 0.6087 14 CDH4_E 0.81597 0.94639 0.84205 0.82789 0.80556 0.70782 53 MAST1 0.91304 0.95411 0.7971 0.84511 0.87681 0.82298 160 MAX.chr20.1784209-1784461 0.57101 0.9686 0.90145 0.6481 0.49275 0.65839 185 RBFOX3_A 0.75652 0.92271 0.86957 0.83967 0.7029 0.58385 262 TRH_A 0.97222 0.94347 0.97168 0.86275 1 0.79012 303 HNF1B_B 0.78472 0.88109 0.83007 0.71895 0.65432 0.73663 116 MAX.chr12.4273906-4274012 0.89855 0.92271 0.90725 0.89258 0.69565 0.63354 170 GAS7 0.77391 0.89614 0.82319 0.74936 0.58696 0.46584 99 MAX.chr5.145725410-145725459 0.90725 0.99758 0.92319 0.85166 0.85145 0.85714 193 MAX.chr5.77268672-77268725 0.85797 0.98551 0.91304 0.90537 0.86232 0.73292 199 GYPC_B 0.68986 0.93478 0.96232 0.72379 0.32609 0.50932 109 DLX6 0.56667 0.91063 0.87246 0.58951 0.70652 0.76708 67 FBN1 0.61739 0.87077 0.94058 0.65473 0.58333 0.79814 91 OSR2_A 0.71304 0.89614 0.90145 0.75703 0.63043 0.74534 234 BEST4 0.69275 0.96377 0.84058 0.91049 0.81884 0.69565 20 AJAP1_B 0.76232 0.84058 0.76232 0.91816 0.73188 0.73913 7 DSCR6 0.98261 0.92512 0.87246 0.86445 0.85507 0.76398 72 MAX.chr11.68622869-68622968 0.50145 0.98792 0.95362 0.7289 0.53623 0.81366 169

TABLE 12 Table 12 shows area under the curve for the identified 80 methylated regions distinguishing basal/triple negative breast tissue, HER2+ breast tissue, Luminal A breast tissue, Luminal B breast tissue, BRCA1 breast tissue, and BRCA2 breast tissue in comparison with normal buffy coat. Basal- DMR Gene Annotation like HER2+ Luminal A Luminal B BRCA1 BRCA2 No. BHLHE23_C 0.83594 0.98026 0.89338 0.82721 0.875 0.80556 23 CALN1_A 0.93555 0.92599 0.84926 1 1 0.88194 36 CD1D 0.74609 0.86184 0.93015 0.86397 0.92708 0.76389 47 CHST2_A 0.73828 0.88651 0.95772 0.73162 0.76563 0.68056 56 FAM126A 0.75781 0.89474 0.93199 0.84743 0.91667 0.86458 83 FMN2 0.77344 0.96053 0.95221 0.78676 0.9375 0.79861 94 HOXA1_A 0.74609 0.97039 0.93015 0.64706 0.64583 0.66667 117 HOXA7_A 0.54297 0.98684 0.87868 0.79044 0.91667 0.84028 119 KCNH8 0.57031 0.98684 0.87132 0.76287 0.77083 0.77778 138 LOC100132891 0.80859 0.99342 0.95221 0.77941 0.875 0.70139 153 MAX.chr1.8277479-8277527 0.82031 0.80592 0.86397 0.87132 1 0.83333 166 MAX.chr15.96889013-96889128 0.87109 0.99013 0.95956 0.95588 1 0.97917 173 NACAD 0.89453 0.91118 0.80147 0.73529 0.90625 0.75 223 SLC30A10 0.75391 0.91118 0.98897 0.65074 0.59375 0.91667 279 TRIM67 0.80664 1 0.8989 0.76654 0.69792 0.78125 305 ATP6V1B1 1 1 1 1 1 1 15 BANK1 0.99609 0.99671 1 0.98529 1 1 17 C10orf125 0.70313 0.88816 0.95588 0.81618 0.875 0.81944 27 C17orf64 0.78906 0.99671 0.94853 0.93015 0.84375 0.95833 29 CHST2_B 0.64453 0.92105 0.91176 0.72426 0.67188 0.70833 57 DLX4 0.93945 0.9227 0.79596 0.94853 0.92188 0.90278 66 DNM3_A 0.71875 0.98684 0.96324 0.79779 0.79167 0.85417 69 EMX1_A 0.80469 0.92763 0.90441 0.75735 0.98958 0.72917 74 FOXP4 1 1 1 1 1 1 96 GP5 1 1 1 0.99265 1 1 104 IGF2BP3_A 0.65625 0.92105 0.86949 0.75919 0.71354 0.75694 123 ITPRIPL1 0.94922 1 0.90809 0.95956 1 0.95833 134 KLHDC7B 1 1 1 0.98897 1 0.98611 146 LMX1B_A 1 0.99671 1 1 1 1 149 MAX.chr11.14926602-14927148 1 0.99342 1 0.99632 1 1 168 MAX.chr5.42994866-42994936 0.94922 0.98026 0.98529 0.99265 1 1 198 MAX.chr8.124173030-124173395 0.98438 0.91118 0.98162 0.98897 1 0.98611 208 MPZ 0.94922 0.99342 0.96691 0.94485 0.90625 0.86111 221 ODC1 0.89453 0.99013 0.97794 0.90074 0.84375 0.875 231 PLXNC1_A 0.94531 0.94408 0.97794 0.88235 0.89583 0.92361 245 PRKCB 0.97266 0.98684 1 1 0.9375 0.86806 256 ST8SIA4 0.99219 1 1 0.98162 1 0.99306 285 STX16_B 1 1 1 1 1 1 289 UBTF 0.99609 0.99671 1 0.99632 1 0.92361 310 LOC100132891 0.8125 0.97697 1 0.84926 1 0.90278 153 ITPRIPL1 0.90234 1 0.95404 0.95221 1 0.9375 134 ABLIM1 0.83398 0.9523 0.8511 0.75919 0.92708 0.88542 3 KLF16 1 0.87171 0.83456 1 0.84375 0.8125 145 MAX.chr12.4273906-4274012 0.90625 0.94737 0.97059 0.97059 0.83333 0.94444 170 MAX.chr12.59990671-59990859 0.78516 0.92434 0.85662 0.63235 0.69792 0.6875 171 MAX.chr19.46379903-46380197 0.78125 0.97697 0.82353 0.88603 0.94792 0.86111 179 ZSCAN12 0.76758 0.88487 0.75 0.78125 0.82292 0.70486 327 AADAT 0.76172 0.85855 0.80147 0.71691 0.89583 0.81944 2 BHLHE23_D 0.71875 0.86184 0.89706 0.87868 0.85417 0.77778 24 COL23A1 0.67969 0.90461 0.8125 0.69118 0.47917 0.93056 60 CXCL12 0.96875 0.97697 0.95221 0.87132 0.98958 0.99306 63 KCNK9 0.92188 0.92434 0.91912 0.71691 0.9375 0.70833 141 LAYN 0.56641 0.97039 0.75735 0.65441 0.625 0.84722 147 OTX1 0.99219 1 1 0.99632 1 1 237 PLXNC1_A 0.81445 0.90625 0.95956 0.76287 0.71875 0.80208 245 RIC3 0.85352 0.96711 0.82353 0.83824 0.89583 0.77778 266 SCRT2_B 0.93359 0.98684 0.83088 0.8364 0.97917 0.61806 273 IGF2BP3_B 0.72656 0.97204 0.90257 0.74632 0.8125 0.81597 124 MAX.chr17.73073682-73073814 1 1 0.93934 0.98529 1 1 174 TBX1 0.99609 1 1 1 1 1 295 ALOX5 0.77539 0.99671 0.87316 0.7739 0.73958 0.81944 9 ASCL2 0.85778 0.92593 0.79556 0.575 0.82222 0.65714 14 CDH4_E 0.87891 0.95724 0.85294 0.85294 0.84375 0.75694 53 MAST1 0.90667 0.96296 0.76444 0.85833 0.86667 0.83333 160 MAX.chr20.1784209-1784461 0.71556 0.98889 0.96 0.73125 0.63333 0.74286 185 RBFOX3_A 0.72 0.90741 0.8 0.7625 0.64444 0.51429 262 TRH_A 1 0.99342 1 0.90809 1 0.97222 303 HNF1B_B 1 1 1 1 1 0.95139 116 MAX.chr12.4273906-4274012 0.9875 0.98611 0.95 0.92647 0.79167 0.88393 170 GAS7 0.93333 0.97917 0.91458 0.86213 0.75 0.79911 99 MAX.chr5.145725410-145725459 0.94583 0.98264 0.92708 0.87868 0.86979 0.91071 193 MAX.chr5.77268672-77268725 0.95417 0.99306 0.96667 0.95588 0.92708 0.875 199 GYPC_B 0.90833 0.99306 1 0.87132 0.76042 0.85714 109 DLX6 0.70208 0.96528 0.95 0.7261 0.83854 0.85268 67 FBN1 0.41667 0.85417 0.94583 0.65074 0.5625 0.79464 91 OSR2_A 0.90417 1 1 0.96507 0.95833 0.91518 234 BEST4 0.69167 0.93403 0.825 0.87132 0.80208 0.74107 20 AJAP1_B 0.675 0.71875 0.675 0.82353 0.65625 0.39286 7 DSCR6 0.97917 0.93056 0.8625 0.89706 0.875 0.80357 72 MAX.chr11.68622869-68622968 0.71458 0.99653 0.97917 0.88603 0.70313 0.88393 169

TABLE 13 Table 13 shows methylation fold change for the identified 80 methylated regions distinguishing basal/triple negative breast tissue, HER2+ breast tissue, Luminal A breast tissue, Luminal B breast tissue, BRCA1 breast tissue, and BRCA2 breast tissue in comparison with normal breast tissue. Basal- DMR Gene Annotation like HER2+ Luminal A Luminal B BRCA1 BRCA2 No. BHLHE23_C 17.39 28.60 15.89 8.07 21.97 5.13 23 CALN1_A 28.82 16.81 15.57 15.63 22.24 9.44 36 CD1D 10.77 16.99 21.18 9.33 13.48 10.65 47 CHST2_A 15.19 82.95 80.41 28.63 13.89 57.16 56 FAM126A 4.45 10.43 31.13 10.07 14.02 30.56 83 FMN2 2.71 27.06 22.58 16.21 24.59 7.57 94 HOXA1_A 20.01 42.46 26.87 14.45 12.63 18.71 117 HOXA7_A 9.72 23.28 15.61 8.19 6.23 7.65 119 KCNH8 1.78 39.32 35.88 14.75 14.13 45.90 138 LOC100132891 185.19 312.06 194.65 143.63 186.82 180.80 153 MAX.chr1.8277479-8277527 9.79 5.38 9.20 7.31 18.72 6.42 166 MAX.chr15.96889013-96889128 6.87 7.87 5.80 5.54 9.78 5.97 173 NACAD 59.72 97.55 3.38 20.96 21.53 22.18 223 SLC30A10 6.66 87.99 105.28 31.45 49.17 88.74 279 TRIM67 86.70 69.09 53.28 43.64 83.52 32.16 305 ATP6V1B1 3.95 2.43 2.52 2.18 3.75 2.52 15 BANK1 2.21 1.49 1.81 1.48 2.17 2.14 17 C10orf125 3.79 18.09 19.60 13.34 16.57 12.82 27 C17orf64 9.30 42.58 15.72 11.05 11.18 24.94 29 CHST2_B 48.81 281.00 298.32 116.70 135.51 191.68 57 DLX4 45.64 60.68 16.25 29.97 41.18 29.75 66 DNM3_A 8.86 23.78 30.08 11.49 18.30 21.56 69 EMX1_A 43.60 122.29 82.84 25.57 49.07 59.72 74 FOXP4 1.88 0.87 1.24 0.91 1.66 1.15 96 GP5 4.39 2.30 2.78 2.43 6.32 2.58 104 IGF2BP3_A 20.99 38.55 29.02 33.09 12.02 26.13 123 ITPRIPL1 68.12 53.72 43.47 51.51 63.79 47.41 134 KLHDC7B 1.31 0.91 1.09 0.79 1.00 0.91 146 LMX1B_A 2.06 2.17 2.14 1.44 2.08 2.32 149 MAX.chr11.14926602-14927148 36.24 22.85 19.10 23.87 28.89 17.02 168 MAX.chr5.42994866-42994936 19.79 13.50 9.94 11.94 21.43 12.21 198 MAX.chr8.124173030-124173395 21.90 24.50 10.92 14.77 28.87 24.86 208 MPZ 123.49 79.48 48.93 74.77 131.51 63.10 221 ODC1 1.78 8.69 8.19 4.66 1.97 7.56 231 PLXNC1_A 7.89 13.76 9.63 8.37 12.31 18.75 245 PRKCB 26.21 38.24 34.42 25.44 26.52 11.10 256 ST8SIA4 0.48 1.05 1.65 0.65 1.13 1.44 285 STX16_B 3.01 1.93 1.96 2.16 3.90 2.88 289 UBTF 1.79 1.77 2.71 1.50 1.93 2.92 310 LOC100132891 9.99 14.86 9.71 8.33 11.87 10.56 153 ITPRIPL1 61.84 47.86 33.92 39.52 46.55 32.55 134 ABLIM1 126.47 140.31 63.32 44.29 132.06 117.33 3 KLF16 25.67 7.34 4.47 7.38 10.97 6.36 145 MAX.chr12.4273906-4274012 301.23 105.51 111.39 153.60 171.56 6.10 170 MAX.chr12.59990671-59990859 28.29 52.80 32.14 14.31 24.76 57.36 171 MAX.chr19.46379903-46380197 22.21 55.50 38.80 19.14 43.26 63.39 179 ZSCAN12 10284.41 4154.53 78.06 4637.92 2760.20 188.89 327 AADAT 1.31 6.34 21.38 14.40 1.47 1.94 2 BHLHE23_D 158.47 264.51 122.98 34.78 124.83 48.69 24 COL23A1 3.98 24.50 27.84 17.76 1.63 29.07 60 CXCL12 2.86 10.36 6.15 6.61 11.71 26.51 63 KCNK9 48.27 85.89 94.77 21.69 46.39 130.44 141 LAYN 16.27 55.56 25.44 23.04 21.03 38.03 147 OTX1 2.80 2.55 2.75 2.26 6.13 4.22 237 PLXNC1_A 22.95 41.20 28.28 29.16 37.81 53.43 245 RIC3 75.70 47.95 37.52 32.73 77.58 16.49 266 SCRT2_B 164.74 109.65 63.97 81.04 101.97 5.69 273 IGF2BP3_B 185.90 412.90 282.64 212.43 385.38 225.97 124 MAX.chr17.73073682-73073814 1.73 0.83 0.85 1.08 1.60 1.84 174 TBX1 1.84 1.42 0.69 0.79 1.41 2.45 295 ALOX5 5.56 22.45 13.11 12.76 8.52 23.22 9 ASCL2 36.06 18.95 24.95 8.63 3.72 22.63 14 CDH4_E 85.74 88.80 89.15 55.48 180.60 66.56 53 MAST1 143.54 82.72 21.57 16.93 93.73 52.01 160 MAX.chr20.1784209-1784461 34.65 76.68 61.27 31.39 29.19 34.67 185 RBFOX3_A 83.13 51.12 56.20 30.74 29.32 41.81 262 TRH_A 13.50 11.59 8.32 9.56 17.69 9.88 303 HNF1B_B 3.02 4.34 2.55 2.40 2.62 4.08 116 MAX.chr12.4273906-4274012 114.75 55.89 51.99 73.21 59.98 9.32 170 GAS7 60.65 32.36 32.26 48.04 33.41 9.47 99 MAX.chr5.145725410-145725459 90.31 118.51 79.19 78.52 136.00 88.88 193 MAX.chr5.77268672-77268725 41.72 50.96 29.95 37.74 65.41 40.86 199 GYPC_B 16.66 22.32 18.77 17.73 4.48 5.49 109 DLX6 91.12 105.35 81.17 31.54 38.38 24.90 67 FBN1 1.41 92.19 132.70 56.35 26.88 122.22 91 OSR2_A 42.34 72.55 32.82 45.53 77.54 58.19 234 BEST4 71.08 73.96 61.71 99.72 85.57 64.51 20 AJAP1_B 28.08 13.72 10.00 20.22 16.87 1.71 7 DSCR6 53.05 52.43 20.76 33.33 36.39 35.57 72 MAX.chr11.68622869-68622968 20.35 111.34 116.50 58.10 30.52 70.46 169

TABLE 14 Table 14 shows methylation fold change for the identified 80 methylated regions distinguishing basal/triple negative breast tissue, HER2+ breast tissue, Luminal A breast tissue, Luminal B breast tissue, BRCA1 breast tissue, and BRCA2 breast tissue in comparison with normal buffy coat. Basal- DMR Gene Annotation like HER2+ Luminal A Luminal B BRCA1 BRCA2 No. BHLHE23_C 128.20 210.78 117.13 59.52 161.94 37.79 23 CALN1_A 106.73 62.24 57.65 57.89 82.38 34.97 36 CD1D 20.42 32.22 40.18 17.70 25.57 20.20 47 CHST2_A 39.29 214.65 208.06 74.08 35.94 147.92 56 FAM126A 55.82 131.03 391.00 126.44 176.02 383.76 83 FMN2 7.46 74.48 62.15 44.63 67.68 20.83 94 HOXA1_A 65.29 138.57 87.67 47.15 41.21 61.06 117 HOXA7_A 33.10 79.29 53.17 27.90 21.23 26.06 119 KCNH8 2.80 61.92 56.51 23.23 22.25 72.29 138 LOC100132891 315.30 531.29 331.39 244.53 318.07 307.81 153 MAX.chr1.8277479-8277527 54.62 30.04 51.31 40.77 104.42 35.83 166 MAX.chr15.96889013-96889128 31.27 35.82 26.39 25.21 44.51 27.19 173 NACAD 7734.43 12633.27 437.58 2714.09 2788.77 2872.49 223 SLC30A10 35.40 467.99 559.93 167.25 261.52 471.97 279 TRIM67 184.28 146.87 113.25 92.76 177.52 68.37 305 ATP6V1B1 135.04 83.03 86.23 74.40 128.07 86.05 15 BANK1 104.87 70.72 85.77 70.16 102.93 101.27 17 C10orf125 18.08 86.39 93.58 63.71 79.10 61.20 27 C17orf64 44.89 205.57 75.89 53.34 53.97 120.40 29 CHST2_B 188.62 1085.94 1152.89 451.00 523.69 740.74 57 DLX4 3920.54 5213.08 1395.77 2574.90 3537.32 2556.10 66 DNM3_A 61.22 164.42 207.92 79.42 126.48 149.04 69 EMX1_A 144.48 405.29 274.54 84.73 162.63 197.93 74 FOXP4 381.51 176.16 251.88 183.64 336.40 232.30 96 GP5 280.65 146.74 178.00 155.65 404.01 164.80 104 IGF2BP3_A 24.63 45.23 34.05 38.83 14.10 30.66 123 ITPRIPL1 84.73 66.82 54.07 64.07 79.34 58.97 134 KLHDC7B 186.31 129.54 154.64 111.99 142.69 129.65 146 LMX1B_A 203.26 213.63 211.34 142.05 204.63 229.02 149 MAX.chr11.14926602-14927148 497.03 313.40 261.90 327.34 396.19 233.42 168 MAX.chr5.42994866-42994936 73.59 50.18 36.95 44.37 79.69 45.39 198 MAX.chr8.124173030-124173395 64.77 72.44 32.29 43.69 85.38 73.51 208 MPZ 249.93 160.87 99.03 151.32 266.15 127.71 221 ODC1 30.64 149.64 141.00 80.25 33.86 130.18 231 PLXNC1_A 106.94 186.43 130.47 113.37 166.70 253.90 245 PRKCB 75.54 110.24 99.23 73.32 76.45 31.99 256 ST8SIA4 38.54 83.88 132.23 51.67 90.22 115.10 285 STX16_B 475.75 305.35 309.74 340.45 615.98 455.10 289 UBTF 125.97 125.03 190.93 105.76 136.15 205.77 310 LOC100132891 25.07 37.29 24.36 20.90 29.79 26.49 153 ITPRIPL1 234.04 181.13 128.39 149.56 176.16 123.19 134 ABLIM1 1223.97 1357.94 612.81 428.63 1278.01 1135.46 3 KLF16 75.80 21.67 13.19 21.78 32.40 18.78 145 MAX.chr12.4273906-4274012 >1 × 10⁶ >1 × 10⁶ >1 × 10⁶ >1 × 10⁶ >1 × 10⁶ >1 × 10⁶ 170 MAX.chr12.59990671-59990859 82.48 153.92 93.68 41.71 72.17 167.20 171 MAX.chr19.46379903-46380197 52.82 132.00 92.28 45.54 102.88 150.76 179 ZSCAN12 2693238 1087971 20443.01 1214559 722829 49466.69 327 AADAT 2.91 14.15 47.72 32.13 3.28 4.33 2 BHLHE23_D 272.07 454.11 211.13 59.71 214.31 83.59 24 COL23A1 4.68 28.80 32.73 20.87 1.91 34.18 60 CXCL12 73.68 266.57 158.26 170.11 301.27 681.91 63 KCNK9 88.62 157.70 174.01 39.83 85.17 239.50 141 LAYN 17.15 58.55 26.81 24.28 22.17 40.08 147 OTX1 118.61 107.72 116.27 95.75 259.48 178.56 237 PLXNC1_A 52.27 93.86 64.43 66.42 86.12 121.71 245 RIC3 187.45 118.73 92.91 81.04 192.10 40.83 266 SCRT2_B 617.81 411.22 239.92 303.91 382.41 21.34 273 IGF2BP3_B 137.82 306.10 209.53 157.48 285.70 167.52 124 MAX.chr17.73073682-73073814 150.82 72.51 74.12 93.99 139.52 159.80 174 TBX1 715.28 553.15 266.62 307.86 548.03 950.84 295 ALOX5 71.55 288.98 168.70 164.22 109.6464 298.90 9 ASCL2 40.30 21.18 27.89 9.65 4.1572 25.29 14 CDH4_E 314.87 326.08 327.36 203.74 663.182 244.42 53 MAST1 232.79 134.16 34.98 27.45 152.0212 84.36 160 MAX.chr20.1784209-1784461 88.90 196.72 157.17 80.52 74.88755 88.94 185 RBFOX3_A 52.90 32.53 35.76 19.56 18.6575 26.60 262 TRH_A 175.90 151.01 108.45 124.56 230.4582 128.70 303 HNF1B_B 31.72 45.52 26.74 25.24 27.46255 42.86 116 MAX.chr12.4273906-4274012 487.31 237.37 220.79 310.90 254.73 39.59 170 GAS7 235.17 125.48 125.07 186.25 129.54 36.70 99 MAX.chr5.145725410-145725459 96.45 126.57 84.58 83.86 145.26 94.93 193 MAX.chr5.77268672-77268725 96.32 117.66 69.15 87.14 151.02 94.34 199 GYPC_B 371.40 497.60 418.40 395.42 99.91 122.49 109 DLX6 364.67 421.64 324.85 126.23 153.59 99.67 67 FBN1 0.76 49.47 71.20 30.24 14.42 65.58 91 OSR2_A 2655.22 4549.99 2058.28 2855.38 4862.64 3648.91 234 BEST4 13.74 14.29 11.93 19.27 16.54 12.47 20 AJAP1_B 3.21 1.57 1.14 2.31 1.93 0.20 7 DSCR6 51.96 51.35 20.34 32.65 35.65 34.84 72 MAX.chr11.68622869-68622968 99.98 547.01 572.37 285.43 149.92 346.17 169

TABLE 15 Table 15 shows AUC, average FC, median FC, and p-value distinguishing DCIS high grade and DCIS low grade. Average Median DMR Gene Annotation AUC FC FC p-value No. SCRT2_B 0.92149 43.36 49.89 <.0001 273 MPZ 0.90083 11.89 23.24 0.0001 221 MAX.chr8.124173030-124173395 0.90083 5.62 8.24 0.0102 208 ITPRIPL1 0.88017 2.47 25.81 0.0903 134 ITPRIPL1 0.87603 3.04 26.71 0.036 134 DLX4 0.85124 5.03 3.99 0.0017 66 CALN1_A 0.82231 5.90 26.11 0.0105 36 IGF2BP3_B 0.81405 5.69 48.23 0.0127 124 LOC100132891 0.78512 2.95 4.82 0.0495 153 MAX.chr5.42994866-42994936 0.7562 4.85 2.10 0.0051 198 MAX.chr11.14926602-14927148 fp 0.73554 1.57 2.51 0.1458 168 PRKCB 0.72314 1.83 2.83 0.1702 256 EMX1_A 0.66529 1.23 21.26 0.7382 74 DNM3_A 0.66116 1.77 2.43 0.1205 69 CHST2_B 0.64876 3.84 5.48 0.0531 57 C10orf125 0.57025 1.24 1.77 0.7431 27

Example I

This example describes the tissue validation of breast-cancer specific markers. Independent tissue samples (fresh frozen) were selected from institutional cancer registries at Mayo Clinic Rochester and were reviewed by an expert pathologist to confirm correct classification and to guide macro-dissection. Cases comprised 29 triple negative/basal-like, 34 HER2 type, 36 luminal A, and 25 luminal B invasive breast cancers. Also included were 5 BRCA1 and 6 BRCA2 cancers, 21 DCIS w/HGD and 12 DCIS w/LGD. Controls included 27 age matched normal breast tissues and 18 buffy coat samples from normal females.

55 methylated DNA markers (MDMs) were chosen from the list of 80 MDMs (see, Example I and Tables 11-15) which were tested on the discovery samples.

Genomic DNA was prepared using QIAamp DNA Mini Kits (Qiagen, Valencia Calif.) and bisulfite converted using the EZ-96 DNA Methylation kit (Zymo Research, Irvine Calif.). Amplification primers were designed from marker sequences using Methprimer software (University of California, San Francisco Calif.) and synthesized commercially (IDT, Coralville Iowa). Assays were rigorously tested and optimized by SYBR Green qPCR (Roche) on bisulfite converted (methylated and unmethylated genomic DNA) and unconverted controls. Assays which cross reacted with negative controls were either redesigned or discarded. Melting curve analysis was utilized to ensure specific amplification was occurring.

qMSP was performed using the LightCycler 480 instrument on 2 uL of converted DNA in a total reaction volume of 25 uL. Standards were derived from serially diluted universal methylated DNA (Zymo Research). Raw marker copies were standardized to CpG-agnostic β-actin, a marker for total genomic DNA.

Results were analyzed logistically using JMP10 (SAS, Cary N.C.). Cases were compared separately to normal breast controls and normal buffy coat samples. Methylation ratios and absolute differentials were calculated for each of the MDMs.

MDM performance in the independent samples was excellent with many AUCs and methylation fold change ratios (FCs) greater than 0.90 and 50, respectively. Results are provided in Table 16A (Triple Negative), 16B (HER2+), 16C (Luminal A), 16D (Luminal D), and 16E (Overall). Here, the MDMs are ranked by AUC (comparing overall cases to buffy coat samples). This is a critical metric for potential application in plasma as the majority of cell-free DNA (cfDNA) originates with leukocytes. Any MDM which does not highly discriminate epithelial-derived cancers from leukocyte DNA will fail in a blood test format, no matter its performance in tissues. 41 of 55 MDMs had cancer v buffy coat AUCs in excess of 0.9, with 3 achieving perfect discrimination (AUC=1). Tables 16A, 16B, 16C, and 16D also list AUCs, FCs, p-values, and % cancer methylation as other critical metrics in evaluating and demonstrating the excellence of these MDMs.

Table 17 highlights the top 10 MDMs for discriminating DCIS HGD from DCIS LGD.

TABLE 16A Triple Negative Gene Annotation AUC p-value % meth FC DMR No. ATP6V1B1 0.91799 <.0001 27.64 3.27 15 FOXP4 0.63653 0.0061 52.73 1.53 96 LMX1B_A 0.77446 <.0001 26.28 3.32 149 BANK1 0.72693 0.0007 23.39 1.84 17 OTX1 0.7987 <.0001 25.43 3.46 237 ST8SIA4 0.69711 0.075 8.34 0.68 285 MAX.chr11.14926602- 0.99441 <.0001 25.03 44.82 168 14927148 UBTF 0.64026 0.0065 25.66 1.87 310 STX16_B 0.59459 0.0021 37.06 2.48 289 KLHDC7B 0.58155 0.1761 23.62 1.25 146 PRKCB 0.88816 <.0001 14.86 32.90 256 TBX1 0.44548 0.7784 14.24 1.06 295 TRH_A 0.95433 <.0001 25.50 9.67 303 MPZ 0.96319 <.0001 21.79 75.65 221 GP5 0.81081 <.0001 26.05 3.53 104 DNM3_A 0.53588 0.0003 9.43 11.61 69 MAX.chr17.73073682- 0.61696 0.0223 26.25 1.58 174 73073814 TRIM67 0.88164 <.0001 11.53 44.19 305 PLXNC1_A 0.56757 <.0001 6.94 10.77 245 MAX.chr12.4273906- 0.95433 <.0001 14.01 64.62 170 4274012 CALN1_A 0.92637 <.0001 14.36 34.56 36 ITPRIPL1 0.73066 <.0001 12.14 26.28 134 MAX.chr12.4273906- 0.91053 <.0001 10.16 299.72 170 4274012 GYPC_B 0.69152 <.0001 9.77 10.05 109 MAX.chr5.42994866- 0.86952 <.0001 12.97 18.90 198 42994936 OSR2_A 0.65284 <.0001 14.65 35.06 234 SCRT2 0.85927 <.0001 10.26 78.29 273 MAX.chr5.145725410- 0.87372 <.0001 8.50 43.77 193 145725459 MAX.chr11.68622869- 0.67102 0.0003 9.03 10.44 169 68622968 MAX.chr8.124173030- 0.79776 <.0001 20.24 2.84 208 124173395 CXCL12 0.47717 0.0347 22.81 3.67 63 MAX.chr20.1784209- 0.64865 <.0001 7.57 23.22 185 1784461 LOC100132891 0.77074 <.0001 10.31 33.46 153 BHLHE23_D 0.80429 <.0001 6.09 94.32 24 ALOX5 0.60951 0.0006 8.79 8.24 9 MAX.chr19.46379903- 0.72693 <.0001 7.50 18.54 179 46380197 ODC1 0.50326 0.0009 5.35 11.28 231 CHST2_B 0.59226 0.0003 6.21 115.56 57 MAX.chr5.77268672- 0.87698 <.0001 11.21 43.30 199 77268725 C17orf64 0.64678 <.0001 19.80 21.95 29 EMX1_A 0.81454 <.0001 8.05 61.16 74 CHST2_A 0.4986 0.0014 4.33 52.73 56 DSCR6 0.83504 <.0001 8.99 92.33 72 ITPRIPL1 0.75676 <.0001 11.13 26.84 134 IGF2BP3_B 0.62302 0.0099 11.34 28.74 124 CDH4_E 0.71016 <.0001 4.40 8.46 53 NACAD 0.77213 <.0001 4.51 40.68 223 DLX4 0.94874 <.0001 26.56 11.40 66 ABLIM1 0.7931 <.0001 6.12 309.82 3 BHLHE23_C 0.71109 <.0001 7.21 64.86 23 MAST1 0.66356 <.0001 11.84 39.32 160 ZSCAN12 0.7754 <.0001 7.32 130.97 327 SLC30A10 0.64585 0.003 4.45 28.19 279 GRASP 0.75862 <.0001 7.85 48.03 105 C10orf125 0.59972 0.0007 7.38 6.46 27

TABLE 16B DMR Gene Annotation HER2+ AUC p-value % meth FC No. ATP6V1B1 0.90143 <.0001 29.30 3.47 15 FOXP4 0.55008 0.1059 43.50 1.26 96 LMX1B_A 0.86725 <.0001 26.35 3.33 149 BANK1 0.80843 <.0001 29.09 2.29 17 OTX1 0.84261 <.0001 27.67 3.76 237 ST8SIA4 0.63275 0.0135 18.88 1.54 285 MAX.chr11.14926602- 0.94913 <.0001 20.82 37.28 168 14927148 UBTF 0.82989 <.0001 45.57 3.32 310 STX16_B 0.62401 0.0042 36.51 2.45 289 KLHDC7B 0.61447 0.0227 28.31 1.50 146 PRKCB 0.9221 <.0001 17.64 39.07 256 TBX1 0.36486 0.8886 14.01 1.04 295 TRH_A 0.95946 <.0001 32.64 12.38 303 MPZ 0.95588 <.0001 26.60 92.35 221 GP5 0.86169 <.0001 40.00 5.43 104 DNM3_A 0.96502 <.0001 29.87 36.79 69 MAX.chr17.73073682- 0.42687 0.7884 17.65 1.06 174 73073814 TRIM67 0.91335 <.0001 10.00 38.35 305 PLXNC1_A 0.86963 <.0001 11.11 17.25 245 MAX.chr12.4273906- 0.84976 <.0001 10.53 48.55 170 4274012 CALN1_A 0.87917 <.0001 12.21 29.38 36 ITPRIPL1 0.95866 <.0001 23.28 50.38 134 MAX.chr12.4273906- 0.8752 <.0001 5.88 173.48 170 4274012 GYPC_B 0.98569 <.0001 20.00 20.57 109 MAX.chr5.42994866- 0.94436 <.0001 12.87 18.76 198 42994936 OSR2_A 0.8283 <.0001 22.48 53.78 234 SCRT2 0.88116 <.0001 7.61 58.12 273 MAX.chr5.145725410- 0.96343 <.0001 13.01 67.01 193 145725459 MAX.chr11.68622869- 0.95151 <.0001 21.77 25.18 169 68622968 MAX.chr8.124173030- 0.81558 <.0001 22.14 3.10 208 124173395 CXCL12 0.60413 0.0012 34.62 5.57 63 MAX.chr20.1784209- 0.96105 <.0001 13.80 42.33 185 1784461 LOC100132891 0.91773 <.0001 22.35 72.51 153 BHLHE23_D 0.84499 <.0001 5.47 84.74 24 ALOX5 0.89587 <.0001 20.49 19.21 9 MAX.chr19.46379903- 0.88394 <.0001 15.20 37.60 179 46380197 ODC1 0.86248 <.0001 10.09 21.29 231 CHST2_B 0.92806 <.0001 15.73 292.49 57 MAX.chr5.77268672- 0.93084 <.0001 12.93 49.95 199 77268725 C17orf64 0.95469 <.0001 32.32 35.82 29 EMX1_A 0.88474 <.0001 11.68 88.73 74 CHST2_A 0.83863 <.0001 8.85 107.82 56 DSCR6 0.94118 <.0001 7.61 78.17 72 ITPRIPL1 0.9531 <.0001 23.40 56.42 134 IGF2BP3_B 0.86606 <.0001 27.94 70.85 124 CDH4_E 0.77424 <.0001 6.06 11.65 53 NACAD 0.78219 <.0001 4.02 36.27 223 DLX4 0.83227 <.0001 32.28 13.86 66 ABLIM1 0.83148 <.0001 6.60 333.82 3 BHLHE23_C 0.84579 <.0001 7.29 65.61 23 MAST1 0.79571 <.0001 14.23 47.24 160 ZSCAN12 0.86248 <.0001 8.11 145.16 327 SLC30A10 0.79849 <.0001 9.87 62.56 279 GRASP 0.8124 <.0001 9.75 59.63 105 C10orf125 0.82273 <.0001 10.54 9.22 27

TABLE 16C DMR Gene Annotation Luminal A AUC p-value % meth FC No. ATP6V1B1 0.86937 <.0001 22.81 2.70 15 FOXP4 0.72222 0.0004 47.80 1.39 96 LMX1B_A 0.89489 <.0001 26.33 3.32 149 BANK1 0.88363 <.0001 30.59 2.41 17 OTX1 0.85736 <.0001 28.06 3.81 237 ST8SIA4 0.82583 <.0001 29.43 2.40 285 MAX.chr11.14926602- 0.84159 <.0001 9.80 17.54 168 14927148 UBTF 0.89865 <.0001 45.16 3.29 310 STX16_B 0.72523 <.0001 42.32 2.84 289 KLHDC7B 0.76426 <.0001 33.45 1.77 146 PRKCB 0.9542 <.0001 24.47 54.19 256 TBX1 0.72297 0.0688 9.74 0.72 295 TRH_A 0.93168 <.0001 27.00 10.24 303 MPZ 0.87725 <.0001 9.40 32.62 221 GP5 0.72823 <.0001 20.40 2.77 104 DNM3_A 0.97748 <.0001 31.67 39.00 69 MAX.chr17.73073682- 0.52177 0.3713 19.47 1.17 174 73073814 TRIM67 0.93619 <.0001 10.08 38.66 305 PLXNC1_A 0.81081 <.0001 14.22 22.09 245 MAX.chr12.4273906- 0.91216 <.0001 11.65 53.72 170 4274012 CALN1_A 0.87012 <.0001 9.36 22.52 36 ITPRIPL1 0.90841 <.0001 12.19 26.37 134 MAX.chr12.4273906- 0.94482 <.0001 5.19 153.20 170 4274012 GYPC_B 0.91742 <.0001 16.59 17.06 109 MAX.chr5.42994866- 0.83859 <.0001 7.69 11.21 198 42994936 OSR2_A 0.82995 <.0001 13.90 33.26 234 SCRT2 0.80143 <.0001 4.15 31.68 273 MAX.chr5.145725410- 0.91066 <.0001 7.10 36.56 193 145725459 MAX.chr11.68622869- 0.94219 <.0001 14.20 16.42 169 68622968 MAX.chr8.124173030- 0.88589 <.0001 19.02 2.66 208 124173395 CXCL12 0.76201 <.0001 46.83 7.54 63 MAX.chr20.1784209- 0.89189 <.0001 9.92 30.44 185 1784461 LOC100132891 0.93956 <.0001 15.50 50.30 153 BHLHE23_D 0.82808 <.0001 4.39 67.94 24 ALOX5 0.83033 <.0001 14.53 13.62 9 MAX.chr19.46379903- 0.83408 <.0001 11.15 27.58 179 46380197 ODC1 0.91967 <.0001 9.20 19.40 231 CHST2_B 0.94557 <.0001 15.06 280.03 57 MAX.chr5.77268672- 0.86186 <.0001 9.93 38.36 199 77268725 C17orf64 0.95495 <.0001 27.43 30.41 29 EMX1_A 0.91366 <.0001 9.89 75.12 74 CHST2_A 0.95646 <.0001 11.32 137.95 56 DSCR6 0.77928 <.0001 3.50 35.98 72 ITPRIPL1 0.89414 <.0001 7.98 19.25 134 IGF2BP3_B 0.9223 <.0001 27.68 70.19 124 CDH4_E 0.81757 <.0001 7.40 14.23 53 NACAD 0.70833 0.0006 2.88 25.92 223 DLX4 0.76877 <.0001 9.95 4.27 66 ABLIM1 0.8217 <.0001 3.92 198.44 3 BHLHE23_C 0.79992 <.0001 5.53 49.76 23 MAST1 0.71096 0.0006 5.15 17.10 160 ZSCAN12 0.67042 0.0114 2.65 47.50 327 SLC30A10 0.90053 <.0001 11.36 71.97 279 GRASP 0.72598 <.0001 4.84 29.64 105 C10orf125 0.88964 <.0001 18.44 16.13 27

TABLE 16D DMR Gene Annotation Luminal B AUC p-value % meth FC No. ATP6V1B1 0.85838 <.0001 27.93 3.31 15 FOXP4 0.59676 0.023 48.67 1.41 96 LMX1B_A 0.90811 <.0001 27.31 3.45 149 BANK1 0.80865 <.0001 31.07 2.45 17 OTX1 0.89838 <.0001 32.49 4.42 237 ST8SIA4 0.62811 0.0286 19.04 1.55 285 MAX.chr11.14926602- 0.99351 <.0001 21.39 38.30 168 14927148 UBTF 0.87784 <.0001 52.44 3.82 310 STX16_B 0.71892 0.0002 39.48 2.65 289 KLHDC7B 0.72432 0.001 34.42 1.82 146 PRKCB 0.91243 <.0001 20.33 45.01 256 TBX1 0.38054 0.372 18.89 1.40 295 TRH_A 0.92649 <.0001 31.24 11.85 303 MPZ 0.95189 <.0001 18.90 65.63 221 GP5 0.77189 <.0001 35.26 4.78 104 DNM3_A 0.89514 <.0001 25.61 31.54 69 MAX.chr17.73073682- 0.58595 0.0507 25.18 1.51 174 73073814 TRIM67 0.92 <.0001 12.08 46.32 305 PLXNC1_A 0.80973 <.0001 8.38 13.02 245 MAX.chr12.4273906- 0.89622 <.0001 12.62 58.22 170 4274012 CALN1_A 0.80541 <.0001 10.14 24.39 36 ITPRIPL1 0.95135 <.0001 21.99 47.60 134 MAX.chr12.4273906- 0.87135 <.0001 5.91 174.39 170 4274012 GYPC_B 0.8973 <.0001 15.82 16.27 109 MAX.chr5.42994866- 0.92973 <.0001 11.46 16.71 198 42994936 OSR2_A 0.92216 <.0001 24.46 58.54 234 SCRT2 0.82216 <.0001 10.65 81.27 273 MAX.chr5.145725410- 0.89351 <.0001 12.41 63.94 193 145725459 MAX.chr11.68622869- 0.93297 <.0001 39.01 45.12 169 68622968 MAX.chr8.124173030- 0.9373 <.0001 27.88 3.91 208 124173395 CXCL12 0.53405 0.0003 64.30 10.35 63 MAX.chr20.1784209- 0.87784 <.0001 17.84 54.72 185 1784461 LOC100132891 0.92541 <.0001 34.07 110.53 153 BHLHE23_D 0.8 <.0001 6.95 107.58 24 ALOX5 0.84432 <.0001 20.19 18.93 9 MAX.chr19.46379903- 0.94054 <.0001 18.28 45.21 179 46380197 ODC1 0.68973 <.0001 5.35 11.29 231 CHST2_B 0.86324 <.0001 10.01 186.17 57 MAX.chr5.77268672- 0.96541 <.0001 15.27 58.97 199 77268725 C17orf64 0.90595 <.0001 32.60 36.14 29 EMX1_A 0.8973 <.0001 15.12 114.84 74 CHST2_A 0.72865 <.0001 6.30 76.74 56 DSCR6 0.92432 <.0001 9.59 98.53 72 ITPRIPL1 0.91135 <.0001 19.45 46.90 134 IGF2BP3_B 0.82973 <.0001 45.42 115.16 124 CDH4_E 0.81838 <.0001 9.05 17.39 53 NACAD 0.75081 0.0002 6.43 57.97 223 DLX4 0.94595 <.0001 21.61 9.28 66 ABLIM1 0.88541 <.0001 4.31 217.96 3 BHLHE23_C 0.8 <.0001 10.48 94.28 23 MAST1 0.77622 <.0001 7.76 25.77 160 ZSCAN12 0.72054 0.0002 15.29 273.71 327 SLC30A10 0.74595 <.0001 8.48 53.74 279 GRASP 0.79459 <.0001 5.88 35.98 105 C10orf125 0.50757 0.0006 6.91 6.04 27

TABLE 17 Table 17 highlights the top 10 MDMs for discriminating DCIS HGD from DCIS LGD. DMR Gene Annotation AUC p-value No. DSCR6 0.9127 <.0001 72 SCRT2 0.86905 0.0314 273 MPZ 0.85714 0.0275 221 MAX.chr8.124173030-124173395 0.84127 0.0122 208 OSR2_A 0.84127 0.0067 234 MAX.chr11.68622869-68622968 0.82143 0.0067 169 ITPRIPL1 0.81746 0.0851 134 MAX.chr5.145725410-145725459 0.81349 0.0037 193 BHLHE23_C 0.80952 0.004 23 ITPRIPL1 0.80556 0.0658 134

All publications and patents mentioned in the above specification are herein incorporated by reference in their entirety for all purposes. Various modifications and variations of the described compositions, methods, and uses of the technology will be apparent to those skilled in the art without departing from the scope and spirit of the technology as described. Although the technology has been described in connection with specific exemplary embodiments, it should be understood that the invention as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications of the described modes for carrying out the invention that are obvious to those skilled in pharmacology, biochemistry, medical science, or related fields are intended to be within the scope of the following claims. 

We claim:
 1. A method, comprising: measuring a methylation level for one or more genes in a biological sample of a human individual through treating genomic DNA in the biological sample with a reagent that modifies DNA in a methylation-specific manner; amplifying the treated genomic DNA using a set of primers for the selected one or more genes; and determining the methylation level of the one or more genes by polymerase chain reaction, nucleic acid sequencing, mass spectrometry, methylation-specific nuclease, mass-based separation, and target capture; wherein the one or more genes comprises a chromosomal region having an annotation that is selected from one of the following groups: (i) BHLHE23_C, CALN1_A, CD1D, HOXA7_A, LOC100132891, MAX.chr1.8277479-8277527, MAX.chr15.96889013-96889128, NACAD, ATP6V1B1, BANK1, C17orf64, DLX4, EMX1_A, FOXP4, GP5, ITPRIPL1, LMX1B_A, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, MAX.chr8.124173030-124173395, MPZ, PRKCB, STX16_B UBTF, LOC100132891, ITPRIPL1, ABLIM1, MAX.chr19.46379903-46380197, ZSCAN12, BHLHE23_D, CXCL12, KCNK9, OTX1, RIC3, SCRT2_B, MAX.chr17.73073682-73073814, CDH4_E, HNF1B_B, TRH_A, MAX.chr20.1784209-1784461, MAX.chr5.145725410-145725459, MAX.chr5.77268672-77268725, BEST4, and DSCR6; (ii) MAX.chr15.96889013-96889128, ATP6V1B1, C17orf64, ITPRIPL1, MAX.chr11.14926602-14927148, MAX.chr5.42994866-42994936, LOC100132891, ITPRIPL1, ABLIM1, MAX.chr19.46379903-46380197, COL23A1, LAYN, OTX1, TRH_A, MAX.chr5.145725410-145725459, and MAX.chr11.68622869-68622968; (iii) ATP6V1B1, MAX.chr11.14926602-14927148, PRKCB, TRH_A, MPZ, GP5, TRIM67, MAX.chr12.4273906-4274012, CALN1_A, MAX.chr12.4273906-4274012, MAX.chr5.42994866-42994936, SCRT2_B, MAX.chr5.145725410-145725459, BHLHE23_D, MAX.chr5.77268672-77268725, EMX1_A, DSCR6, and DLX4; (iv) ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, GP5, DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197, ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, CHST2_B, DSCR6, ITPRIPL1, IGF2BP3_B, DLX4, ABLIM1, BHLHE23_D, ZSCAN12, GRASP, and C10orf125; (v) ATP6V1B1, LMX1B_A, BANK1, OTX1, ST8SIA4, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_D, ALOX5, MAX.chr19.46379903-46380197, ODC1, CHST2_A, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, CHST2_B, ITPRIPL1, IGF2BP3_B, CDH4_E, ABLIM1, SLC30A10, C10orf125; (vi) ATP6V1B1, LMX1B_A, BANK1, OTX1, MAX.chr11.14926602-14927148, UBTF, PRKCB, TRH_A, MPZ, DNM3_A, TRIM67, PLXNC1_A, MAX.chr12.4273906-4274012, CALN1_A, ITPRIPL1, MAX.chr12.4273906-4274012, GYPC_B, MAX.chr5.42994866-42994936, OSR2_A, SCRT2_B, MAX.chr5.145725410-145725459, MAX.chr11.68622869-68622968, MAX.chr8.124173030-124173395, MAX.chr20.1784209-1784461, LOC100132891, BHLHE23_C, ALOX5, MAX.chr19.46379903-46380197, CHST2_B, MAX.chr5.77268672-77268725, C17orf64, EMX1_A, DSCR6, ITPRIPL1, IGF2BP3_B, CDH4_E, DLX4, ABLIM1, BHLHE23_D; and (vii) DSCR6, SCRT2_B, MPZ, MAX.chr8.124173030-124173395, OSR2_A, MAX.chr11.68622869-68622968, ITPRIPL1, MAX.chr5.145725410-145725459, BHLHE23_C, ITPRIPL1. 